Method and its apparatus for inspecting particles or defects of a semiconductor device

ABSTRACT

An apparatus for inspecting particles and/or pattern defects of an object under inspection. Data processing means obtains information on size of the particles and/or the pattern defects from an intensity of the scattered light detected by the light detecting means by referring to a relationship between an intensity of scattered light from a standard particle and a size of the standard particle, and using a calibration coefficient for compensating for a change in intensity of the light of the illuminating means from a predetermined intensity.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation of application Ser. No. 11/190,838,filed Jul. 28, 2005 now U.S. Pat. No. 7,262,425, which is a continuationof application Ser. No. 10/230,416, filed Aug. 29, 2002 (now U.S. Pat.No. 6,936,835), which is a continuation-in-part of application Ser. No.09/931,997 filed on Aug. 17, 2001 (now U.S. Pat. No. 6,797,975. Thisapplication relates to and claims priority from Japanese PatentApplication No. 2001-288013, filed on Sep. 21, 2001 and No. 2000-291952,filed on Sep. 21, 2000. The entirety of the contents and subject matterof all of the above is incorporated herein by reference.

BACKGROUND OF THE INVENTION

The present invention relates to a method and apparatus for inspectingparticles and/or defects, and more particularly, to a method andapparatus for inspecting particles and/or defects for use in inspectingparticles existing on thin film substrates, semiconductor substrates,photomasks and so on, and pattern defects encountered on patterns onsuch materials, and analyzing the cause of the defects in themanufacturing of semiconductor chips (dies) and liquid crystal products,wherein the method and apparatus of the invention display an inspectionresult in such a form that enables the user to readily analyze theresult and rapidly identify the cause of failure.

Conventionally, the technology for detecting defects on semiconductordevices and so on using an optical measuring means has been widelyknown. For example, “Semiconductor Wafer Inspection Apparatus” describedin JP-A-62-89336 discloses a technique for irradiating a semiconductorsubstrate with a laser to detect scattered light from particles, ifattached on the semiconductor substrate, and comparing the detectedscattered light with the result of an inspection, which has been madeimmediately before on the same type of semiconductor substrate, toinspect the particles and/or defects.

Also, “Method and Apparatus for Measuring Information on Particle ordefect Size” described in JP-A-5-273110 discloses a method of measuringsizes of particles or crystal defects, which involves irradiating anobject under inspection with a laser beam, receiving scattered lightfrom possible particles or crystal defects on the object underinspection, and processing the scattered light to generate an image ofthe object under inspection on which the sizes of particles and crystaldefects are measured.

Also, “Yield Monitoring and Analysis in Semiconductor Manufacturing” inprescripts of VLSI technology Seminar, pp. 4-42-4-47, in SEMICON Kansai,1997, discloses an approach for analyzing the yield from particlesdetected on a semiconductor wafer.

Conventionally, as an approach for managing product manufacturingprocesses in manufacturing lines for semiconductor substrates, thin filmsubstrates and so on, a management approach is employed for monitoringparticles and defects on substrates. Such a monitoring method involvesinspecting particles or pattern defects on substrates by use of anapparatus for inspecting particles and/or defects, monitoring atransition of the number of particles and/or defects detected by theinspection apparatus, and conducting a failure analysis on the particlesand/or defects on substrates, from which a large number of particlesand/or defects have been detected.

However, this prior art approach requires a total time for the failureanalysis equal to the product of the number of detectedparticles/defects and a time required for the failure analysis on oneparticle/defect. Particularly, the failure analysis requires aprohibitively long time when the particle/defect inspection apparatusdetects a large number of particles and/or defects, thereby giving riseto a problem that the manufacturing of substrates is delayed.

SUMMARY OF THE INVENTION

The present invention has been made to solve the problem of the priorart as mentioned above, and provides a method and apparatus forinspecting particles and/or defects for use in inspection and failureanalysis on processes for manufacturing semiconductor wafers and thinfilm substrates, which are capable of performing an inspection inaccordance with sizes of particles and pattern defects or thecharacteristics of each region on an object under inspection to takeprompt countermeasures to a failure.

Specifically, the present invention provides a particle/defectinspection apparatus for measuring an object under inspection inaccordance with an optical approach to detect particles and/or defectsthereon. The inspection apparatus includes illuminating means forilluminating light to an object under inspection, light detecting meansfor detecting reflected light and/or scattered light from the objectunder inspection, detecting means for detecting particles and/or defectsbased on a signal detected by the light detecting means, dimensionmeasuring means for processing the signal detected by the lightdetecting means to measure the size of each particle and/or defect, dataprocessing means for processing an inspection result, and display meansfor displaying information on the inspection result, wherein the dataprocessing means relates a particle and/or defect size to a cause offailure to point out the cause of failure from statistical processing onthe inspection result, and the display means displays information on theinspection result.

In an aspect of the present invention, for example, the means fordisplaying information on the inspection result displays an occurrencefrequency distribution of the particles or the pattern detects ofrespective sizes obtained by the dimension measuring means.

Further, in another aspect of the present invention, the means fordisplaying information on the inspection result displays information onthe particles and/or the pattern defects of a given range of size in amanner discriminative from information on the particles and/or thepattern defects of another range of size.

Further, in a still another aspect of the present invention, managementinformation is provided for each of the regions on the object underinspection. The management information is compared with the size of aparticle and/or a pattern defect detected from each of the regions, andevaluation as to whether each of the regions on the object underinspection is defective or non-defective in quality is made, therebyconducting a failure analysis for each of the regions on the objectunder inspection.

Still further, in other aspect of the present invention, the objectunder inspection is managed for each of the regions on the object underinspection, and the means for displaying information on the inspectionresult displays for each of the regions an occurrence frequencydistribution of respective sizes of the particles and/or the patterndefects obtained by the dimension measuring means.

In still other aspect of the present invention, the means for displayinginformation on the inspection result can display the yield impact, thatis the influence of particles and/or pattern defects on a yield, basedon the sizes of the particles and/or the pattern defects obtained by thedimension measuring means and information on defectiveness ornon-defectiveness of electric characteristics, obtained from theelectric inspection of the object under inspection.

The present invention also provides a particle/defect inspecting methodfor measuring an object under inspection in accordance with an opticalapproach to detect particles and/or defects thereon. The inspectingmethod includes a procedure for illuminating light to an object underinspection, a procedure for detecting reflected light and/or scatteredlight from the object under inspection, a procedure for detectingparticles and/or defects based on a detected signal, a procedure forprocessing the detected signal to measure the size of each particleand/or defect, a data processing procedure for processing an inspectionresult, and a procedure for displaying information on the inspectionresult. The procedures are executed in this order to relates a particleand/or defect size to a cause of failure, wherein the data processingprocedure points out a cause of failure from statistical processing onthe inspection result to display information on the inspection result.

In an aspect of the present invention, for example, when displayinginformation on the inspection result, an occurrence frequencydistribution of respective sizes of the particles or the pattern detectsobtained by the dimension measuring step is displayed.

Further, in another aspect of the present invention, when displayinginformation on the inspection result, information on the particlesand/or the pattern defects of a given range of size is displayed in amanner discriminative from information on the particles and/or thepattern defects of another range of size.

Further, in a still another aspect of the present invention, managementinformation is provided for each of the regions on the object underinspection. The management information is compared with the size of aparticle and/or a pattern defect detected from each of the regions, andevaluation as to whether each of the regions on the object underinspection is defective or non-defective in quality is made, therebyconducting a failure analysis for each of the regions on the objectunder inspection.

Still further, in other aspect of the present invention, the objectunder inspection is managed for each of the regions on the object underinspection, and when displaying information on the inspection result, anoccurrence frequency distribution of respective sizes of the particlesand/or the pattern defects obtained by the dimension measuring step isdisplayed for each of the regions.

In still other aspect of the present invention, the means for displayinginformation on the inspection result can display the yield impact ofparticles and/or pattern defects on a yield, based on the sizes of theparticles and/or the pattern defects obtained by the dimension measuringmeans and information on defectiveness or non-defectiveness of electriccharacteristics, obtained from the electric inspection of the objectunder inspection.

These and other objects, features and advantages of the invention willbe apparent from the following more particular description of preferredembodiments of the invention, as illustrated in the accompanyingdrawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram generally illustrating the configuration of anapparatus for inspecting particles and/or defects according to thepresent invention;

FIG. 2 is a block diagram of the apparatus for inspecting particlesand/or defects according to the present invention when it is operated asa component of a system;

FIG. 3A is a diagram showing image data when a particle exists;

FIG. 3B is a three-dimensional graph showing a distribution of intensitywhen particle data is measured;

FIGS. 4A and 4B are three-dimensional graphs for comparing distributionsof two types of intensitys;

FIG. 4C is a graph for explaining how a maximum is calculated for theintensity;

FIGS. 5A to 5C are graphs showing the relationship between the particlesize and the number of detected particles depending on different causesof failure;

FIG. 6 is a graph showing the relationship between the number ofdetected particles and the particle size;

FIG. 7 is a histogram showing the relationship between the number ofdetected particles and the particle size;

FIGS. 8A and 8B are diagrams clearly illustrating particles of aparticular size on a wafer;

FIGS. 9A to 9C are graphs each showing in time series a transition ofthe number of detected particles having a particular size;

FIG. 10 is a front view of a screen which displays for the user a causeof failure which results in the generation of particles;

FIG. 11 is a plan view schematically illustrating regions on asemiconductor wafer;

FIGS. 12A and 12B are plan views each clearly showing particles of aparticular size on a wafer when particle data is managed separately foreach region;

FIG. 13 is a graph (No. 1) showing the relationship between the particlesize and the number of detected particles in each of regions;

FIG. 14 is a graph (No. 2) showing the relationship between the particlesize and the number of detected particles in each of regions;

FIG. 15 is a graph for explaining the relationship between a maximum ofintensity generated by the apparatus for inspecting particles and/ordefects according to the present invention and the particle size;

FIG. 16 is a block diagram illustrating the apparatus for inspectingparticles and/or defects according to the present invention which isoperated as a system together with a review apparatus;

FIG. 17A is a three-dimensional graph showing a distribution of asaturated intensity;

FIG. 17B is a graph for explaining how a maximum is calculated for theintensity;

FIG. 17C is a plan view of a particle showing a major axis and a minoraxis of the particle;

FIG. 18A is a block diagram generally illustrating the configuration ofan inspection apparatus which has a function of distinguishing particlesfrom scratches;

FIG. 18B is a diagram for explaining a method of distinguishingparticles from scratches;

FIG. 19 is a block diagram illustrating a method of calculating theparticle size when using the method of distinguishing particles fromscratches;

FIG. 20 is a histogram showing the relationship between the number ofdetected particles and the particle size for a plurality of objectsunder inspection;

FIG. 21 is a histogram showing the relationship between the number ofdetected particles/scratches and the particle/scratch size separatelyfor particles and scratches;

FIG. 22 is a front view of a display showing a method of displayingdetected particles of particular sizes in the apparatus for inspectingparticles and/or defects according to the present invention;

FIG. 23 is a plan view of a wiring pattern for explaining therelationship between the wiring pattern and a particle size;

FIG. 24 is a graph showing the relationship between a detectionsensitivity and the yield impact of particles on a yield, when theapparatus for inspecting particles and/or defects according to thepresent invention is used;

FIG. 25 is a graph showing an example of calculating the yield impactfor each manufacturing step;

FIG. 26 is a graph showing the relationship between the particle sizeand the number of detected particles when standard particles aremeasured by the apparatus for inspecting particles and/or defectsaccording to the present invention;

FIG. 27 is a graph showing the relationship between the particle sizeand the number of detected particles before calibrating the sensitivityfor the size of detectable particles in the apparatus for inspectingparticles and/or defects according to the present invention;

FIG. 28 is a graph showing the relationship between particle sizesmeasured by the inspection apparatus according to the present inventionand sizes measured by SEM when the sensitivity for the size ofdetectable particles is calibrated in the apparatus for inspectingparticles and/or defects according to the present invention;

FIG. 29 is a plan view of a wafer for explaining a method of calculatingthe yield impact from the presence or absence of particles;

FIGS. 30A and 30B are graphs showing correlations of particle sizesmeasured by the apparatus for inspecting particles and/or defectsaccording to the present invention to particle sizes measured by SEM,where FIG. 30A shows a correlation of particle sizes measured on a waferhaving a one-layer pattern to particle sizes measured by SEM, and FIG.30B is a graph showing a correlation of particle sizes measured on awafer having a multi-layer pattern to particle sizes measured by SEM;

FIG. 31 includes a graph showing a correlation of particle sizesmeasured by the apparatus for inspecting particles and/or defectsaccording to the present invention to particle sizes measured by SEM,and SEM photographs of detected particles;

FIG. 32 is a histogram showing the relationship between particle sizesand the number of the particles measured by the apparatus for inspectingparticles and/or defects according to the present invention;

FIG. 33A is a graph showing the relationship between particle sizesmeasured by the apparatus for inspecting particles and/or defectsaccording to the present invention, and the yield;

FIGS. 33B and 33C are plan views of wafers each showing a distributionof detected particles on the wafer;

FIG. 34 is a graph showing an exemplary display of the accumulatednumber of particles by size, using the apparatus of inspecting particlesand/or defects according to the present invention;

FIG. 35 is a graph showing the relationship between particle sizes andthe number of the particles measured by the apparatus for inspectingparticles and/or defects according to the present invention, togetherwith a distribution of the detected particles;

FIG. 36 is a graph showing the relationship between the particle sizeand the detected particle quantity rate as the result of particledetection by the apparatus for inspecting particles and/or defectsaccording to the present invention;

FIG. 37 is a graph showing the relationship between the particle sizeand the accumulated number of particles as the result of particledetection by the apparatus for inspecting particles and/or defectsaccording to the present invention;

FIG. 38 is a graph showing the relationship between the particle sizeand the accumulated particle quantity ratio as the result of particledetection by the apparatus for inspecting particles and/or defectsaccording to the present invention;

FIG. 39 is a graph showing the relationship between the particle sizeand the number of detected particles as the result of particle detectionby the apparatus for inspecting particles and/or defects according tothe present invention;

FIG. 40 is a graph showing the relationships between the particle sizeand the number of detected particles for a plurality of wafers, asresults of detection by the apparatus for inspecting particles and/ordefects according to the present invention;

FIG. 41 is a graph showing the relationship between the minimum detectedparticle size and the proportion of an inspection area;

FIGS. 42A and 42B are diagrams showing an image of a particle and adistribution of contrast values of the image in FIG. 42A, respectively;

FIGS. 43A and 43B are front views of a display screen showing examplesof display as the results of particle detection according to the presentinvention;

FIG. 44 is a block diagram when the apparatus for inspecting particlesand/or defects according to the present invention is operated as asystem in semiconductor device manufacturing lines;

FIG. 45 is a three-dimensional representation of a Gaussian distributionfor explaining the method of correcting a saturated signal value;

FIGS. 46A to 46C are graphs showing the relationships between the amountof scattered light from a particle and/or a defect, caused byvertical-illumination, and the amount of scattered light from theparticle or the defect, caused by oblique illumination;

FIGS. 47A and 47B are graphs that respectively employ characteristicamounts 1 and 2 and characteristic amounts 3 and 4, for discriminationbetween particles and defects;

FIGS. 48A and 48B are graphs showing the relationship between theintensity of scattered light from a particle and the measured size, andthe relationship between the intensity of scattered light from a defectand the measured size, respectively;

FIG. 49 is a front view of a display screen showing examples of displaywhen discrimination between particles and defects has been made by theapparatus for inspecting particles and/or defects according to thepresent invention;

FIG. 50 is a front view of the display screen showing another examplesof display when discrimination between particles and defects has beenmade by the apparatus for inspecting particles and/or defects accordingto the present invention;

FIG. 51 is a diagram explaining an approach to determining the size of aparticle to be managed, by the apparatus for inspecting particles and/ordefects according to the present invention;

FIG. 52 is a graph showing the relationship between the particle sizethreshold and the yield impact;

FIG. 53 is a graph showing the relationship among the particle sizethreshold, yield impact, critical probability, and quantity rate ofchips on which a particle has been detected;

FIG. 54 is a graph showing the relationship between the particle sizethreshold and the yield impact in the apparatus for inspecting particlesand/or defects according to the present invention;

FIGS. 55A and 55B are graphs showing the relationship between theparticle size threshold and the yield impact for each of inspectionapparatuses; and

FIG. 56 is a graph showing relationships between the particle sizethreshold and the yield impact for three apparatuses for inspectingparticles and defects according to the present invention.

DESCRIPTION OF THE EMBODIMENTS

In the following, each of embodiments according to the present inventionwill be described with reference to the accompanying drawings.

Configuration and Operation of Apparatus for Inspecting Particles and/orDefects According to the Present Invention

First, the configuration and operation of an apparatus for inspectingparticles and/or defects according to the present invention will bedescribed with reference to FIGS. 1 and 2.

FIG. 1 is a block diagram illustrating the configuration of theapparatus for inspecting particles and/or defects according to thepresent invention.

FIG. 2 is a block diagram of the apparatus for inspecting particlesand/or defects according to the present invention when it is operated asa component of a system.

While the following description on the embodiment will be made on anexample in which a semiconductor wafer is inspected for particlespossibly attached thereon, the present invention can be applied to anapparatus for inspecting pattern defects other than particles. Also, thepresent invention is not limited to semiconductor wafers but can beapplied to thin film substrates, photomasks, TFT, PDP and so on.

The apparatus for inspecting particles and/or defects according to thepresent invention comprises an illumination optical system 101; adetection optical system 103; a light detector unit 104; a signalprocessing circuit 105; a data display unit 106; a stage assembly 107;an auto-focus illumination unit 108; and an auto-focus light receiverunit 109.

For conducting an inspection, an object under inspection 102 is placedon the stage assembly 107 and irradiated by the illumination opticalsystem 101, and scattered light from the object under inspection 102 iscondensed by the detection optical system 103. Then, the light detectorunit 104 detects the scattered light from the object under inspection102. The scattered light detected by the light detector unit 104 isopto-electrically transduced, and processed by the signal processingcircuit 105 to detect particles and measure their sizes.

The object under inspection 102 is moved in the horizontal direction bythe stage assembly 107, and also moved in the vertical direction by theauto-focus illumination unit 108 and auto-focus light receiver unit 109such that the object under inspection 102 is positioned at the focalpoint of the detection optical system 103. Thus, particles can bedetected and their sizes be measured over the entire area of the objectunder inspection 102. Then, the result of detection is displayed on thedata display unit 106.

Here, the illumination optical system 101 is configured to irradiate theobject under inspection 102 with light, for example, from a laser lightsource such as Ar laser, semiconductor laser, YAG laser and UV laser, ora white light source such as an Xe lamp and Hg lamp, using a beamexpander, a collimator lens, a cylindrical lens or the like. Theillumination optical system 101 is adjusted such that the light isirradiated at the focal point of the detection optical system 103.

Here, for selecting an appropriate light source, a light source having ashort wavelength is preferred as the illumination light source forimproving the sensitivity for detecting particles, so that a YAG laser,Ar laser and UV laser are suitable. Alternatively, for reducing the sizeand cost of the apparatus, a semiconductor laser is suitable. Furtheralternatively, a white light source is suitable as the illuminationlight source for reducing interference by an optically transparent thinfilm which may be formed on an object under inspection.

As to the shape of irradiating light, a circular illumination or a linerillumination may be used for irradiation. The illumination light may beor may not be collimated light. For increasing the amount of light on anobject under inspection per unit area, the power of the illuminationlight source may be increased, or the illumination light may beilluminated with high numerical aperture (NA).

Next, the detection optical system 103 has optical lenses configuredsuch that from the light emitted from the illumination optical system101, scattered light from the object under inspection 102 is condensedon the light detector unit 104. Also, the detection optical system 103also has the ability to optically process the scattered light, forexample, make modification, adjustment and so on to the opticalcharacteristics of the scattered light using a polarizer and a spatialfilter.

When a polarizer is used for optical processing, the polarizer ispreferably set up in a direction in which P-polarized light istransmitted when S-polarized light is irradiated. On the other hand, thepolarizer is preferably set up on a direction in which S-polarized lightis transmitted when P-polarized light is irradiated. When a spatialfilter is used, collimated light is suitably used as the illuminationlight for improving the performance of detecting particles.

The light detector unit 104 is used to receive the scattered lightcondensed by the detection optical system 103 for opto-electricallytransducing the scattered light, and is implemented, for example, by aTV camera, a CCD linear sensor, a TDI sensor, an anti-blooming TDIsensor, and a photomultiplier.

For selecting a device for the light detector unit 104, aphotomultiplier is suitable in use for detecting feeble light.Alternatively, a TV camera is suitable for rapidly capturing atwo-dimensional image. When the detection optical system 103 comprises afocusing system, a TV camera, a CCD linear sensor, a TDI sensor, or ananti-blooming TDI sensor is suitable. When the detection optical system103 comprises a light condenser system, a photomultiplier may be used.In addition, when the light detector unit 104 receives light over a widedynamic range, i.e., if the sensor is saturated by incident light, thesensor may be additionally provided with an anti-blooming function.

Next, the signal processing circuit 105 has a section for detectingparticles, a section for measuring the size of a particle, and an outputportion for outputting measured data to the data display unit 106 and/ora network 1306. For detecting particles, the signal processing circuit105, for example, binarizes an input signal, determines a signal equalto or larger than a binarization threshold as a particle, and outputsthe result of determination. While the signal processing circuit 105also measures particle sizes, details on associated processing will bedescribed later. The stage assembly 107 in turn has functions of, forexample, moving the object under inspection 102 in the horizontal andvertical directions, and rotating the object under inspection 102. Theauto-focus illumination unit 108 converges light emitted, for example,from a white light source such as an Hg lamp or a laser light sourcesuch as He—Ne onto the object under inspection 102. Here, the wavelengthof a light source used in the auto-focus illumination unit 108 ispreferably different from that of a light source used in theillumination optical system 101.

Next, the auto-focus light receiver unit 109 is a section for receivinga portion of emitted from the auto-focus illumination unit 108, which isreflected from the object under inspection 102, and may comprise asensor capable of detecting the position of light, such as a positionsensor. Information acquired by the auto-focus light receiver unit 109is sent to the stage assembly 107 for controlling the stage. While inthe embodiment illustrated in FIG. 1, the illumination optical system101 illuminates the object under inspection 102 from one direction, theillumination optical system 101 may be configured to illuminate theobject under inspection 102 from two directions. Further, while theexample of FIG. 1 has one each of the detection optical system 103 anddetector unit 104 to detect the object under inspection 102 in onedirection, the inspection apparatus may comprise two or more sets ofthese components such that the object under inspection 102 is detectedin two or more directions.

Next, methods of setting conditions for detecting particles and/ordefects when the particle size is employed in the apparatus forinspecting particles and/or defects according to the present inventionwill be described. There are some conditions required for setting, suchas an optical condition and a condition in signal processing. In thisembodiment, a method of setting an illumination source and anirradiation intensity will be described by way of an example.

Suppose that the amount of light reflected from circuit patterns printedon an object under inspection and then supplied to the light detectorunit is proportional to the irradiation intensity of the illuminationsource in the apparatus for inspecting particles and/or defects. If theirradiation intensity of the illumination source is increased, theamount of the light reflected from the circuit patterns will increase,thereby saturating the opto-electrical transducing elements of the lightdetector unit. When the reflected light from the circuit patterns hassaturated the light detector unit, a signal obtained from the circuitpatterns will assume a value that saturates the light detector unit.Accordingly, regardless of the presence or absence of a particle on thecircuit patterns, the value of the signal will remain the same. For thisreason, no particles on the circuit patterns cannot be detected. Inother words, if the irradiation intensity of the illumination source isincreased, circuit patterns from which no particles can be detected willincrease, thereby reducing the areas where particles can be detected.

The degree of a decrease in the areas where particles can be detectedvaries according to the reflectivities of materials employed formanufacture of the circuit patterns, complexity of a circuit patternstructure, and the optical processing method as well as the irradiationintensity of the illumination source. When the area from which particlescan be detected varies according to the irradiation intensity of theillumination source in this way, a detection condition should bedetermined by using a graph illustrated in FIG. 41. First, descriptionwill be directed to FIG. 41. FIG. 41 is the graph which sets the minimumsize of a particle to be detected on the horizontal axis, and aproportion of the area on which particles can be detected to the entirearea of an object under inspection on the vertical axis. This embodimentshows the case where the area on which particles can be detected isdecreased with an increase in the irradiation intensity of theillumination light source, though smaller particles can be detected.

A curve 4101 in FIG. 41 shows proportions of areas to the entire objectarea, where detection of particles of sizes equal to or larger thanthose set on the horizontal axis is possible. In this embodiment, 0.1 μmon the horizontal axis represents a condition where a particle having asize equal to or more than 0.1 μm is detected. In this case, in order toallow particle detection, it is necessary to increase the irradiationintensity of the illumination light source. Thus, light reflected from alot of circuit patterns saturates the light detector unit, so that thepercentage of the area from which particles can be detected to theentire object area becomes 15%. Further, when a condition for detectinga particle having a size equal to or more than 1 μm is determined,particles can be detected even if the irradiation intensity of theillumination light source is small. Thus, the amount of light reflectedfrom the circuit patterns is reduced, so that the number of the circuitpatterns that bring about saturation of the light detector unit isreduced. Accordingly, particle detection is possible in 85% of theentire area of the object under inspection.

The operator of the apparatus for inspecting particles and/or defectsaccording to the present invention can determine a desired detectioncondition if he specifies the size of a particle to be detected or thepercentage of a particle detectable area, from the graph in FIG. 41. Ifthe operator specifies the percentage of the particle detectable area tobe 50%, the apparatus for inspecting particles and/or defects accordingto the present invention automatically sets the irradiation intensity atwhich 0.65 μm particles can be detected. The relationship between thesize of a particle to be detected and the irradiation intensity of theillumination light source should be measured in advance by the apparatusfor inspecting particles and defects according to the present invention.

Since the shape of the curve 4101 in FIG. 41 varies according to anobject under inspection, measurement should be performed for each objectunder inspection. As a measuring method, the amount of light reflectedfrom an object under inspection may actually be measured and then asaturation area may be thereby measured. Alternatively, design data mayalso be employed to calculate a saturation area if the saturation areacan be anticipated from the design data on an object under inspection.The former method does not need the design data, so that it can beemployed for measurement if only an object under inspection isavailable, while the latter method can set a detection condition inadvance, so that it can reduce a condition setting time.

In this example, description was given about the method of setting thecondition of the irradiation intensity of the illumination light sourcebased on the size of a particle to be detected. A method of changing athreshold value for signal processing based on the size of a particle tobe detected may also be employed. In this case, suppose the apparatusfor inspecting particles and defects where the irradiation intensity ofthe illumination light source is kept to be constant and detection ofparticles is made to be more difficult as the threshold value forparticle detection is set to be larger, for example. Then, if only largeparticles have to be detected, the threshold should be set to be large,while on the contrary, if even small particles have to be detected, thethreshold should be set to be small.

Next, a system in semiconductor device manufacturing lines will bedescribed with reference to FIG. 44. FIG. 44 shows semiconductor devicemanufacturing processes 4401, an inspection process 4402, inspectionapparatuses 4403 for inspecting particles and/or defects, a database4404, and measuring apparatuses 4405 for managing process states.

The inspection apparatuses 4403 are the apparatuses for inspectingparticles and defects according to the present invention, for example,for detecting particles and/or defects or classifying the particlesand/or defects. The measuring apparatuses 4405 comprise, for example, anapparatus for determining defectiveness or non-defectiveness of asemiconductor device by means of an electric test, an apparatus forconducting a component analysis, an apparatus for measuring thethickness of a film applied onto a semiconductor device, an apparatusfor measuring a pattern width formed on the semiconductor device, anapparatus for measuring electric conductivity between patterns, and areview apparatus for the particles and/or defects. The database 4404stores the results of inspection by the inspection apparatuses 4403,results of measurement by the measuring apparatuses 4405, information onthe semiconductor device manufacturing processes, and instances of thepast defects.

Next, operations in the semiconductor device manufacturing system inFIG. 44 will be described. First, semiconductor devices are manufacturedin accordance with the semiconductor device manufacturing processes4401, undergoing respective processes included therein. During thecourse of the device manufacturing process, defect inspection isperformed in the inspection process 4402. If a defect is encountered,the result of inspection is compared with the information in thedatabase 4404 and the results of measurement by the measuringapparatuses 4405, and then countermeasures against the defect are fedback to the semiconductor device manufacturing processes 4401.

Next, FIG. 2 illustrates a system which is configured using theapparatus for inspecting particles and/or defects according to thepresent invention. Specifically, the system comprises the particleinspection apparatus 1301 of the present invention; a data server 1302;a review apparatus 1303; an electric testing apparatus 1304; an analyzer1305; and a network 1306 for interconnecting the respective components.In this system, the review apparatus 1303 is, for example, a measuringSEM; the electric testing apparatus 1304 is a tester; and the analyzer1305 is an apparatus for analyzing components of particles such as EDX.The data server 1302 is a computer which can collect and accumulateinspection data from the particle inspection apparatus 1301; results ofreviews from the review apparatus 1303; results of tests from theelectric testing apparatus 1304; and results of analyses from theanalyzer 1305. The network 1306 is a communication network, for example,based on the Ethernet.

Next described will be the operation of the system using the apparatusfor inspecting particles and/or defects. After an inspection has beenmade in the particle inspection apparatus 1301, particles for whichappropriate countermeasures should be taken are selected by a method asdescribed later. Information indicative of necessity of thecountermeasures is added to the result of inspection by the particleinspection apparatus 1301, for example, serial numbers allocated toparticles when they were detected, information on the positions ofparticles, information on the sizes of particles, and so on, andtransmitted to the data server 1302 through the network 1306. For addingthe information indicative of necessity of the countermeasures, forexample, a flag may be added to the result of detection to indicatewhether or not appropriate countermeasures are required. Then, forinvestigating particles detected by the particle inspection apparatus1301 in greater detail, the object under testing is conveyed to thereview apparatus 1303. The object under testing may be manually conveyedor mechanically conveyed.

After the object under testing has been conveyed to the review apparatus1303, the review apparatus 1303 accesses the data server 1302 to receivethe result of detection from the data server 1302 through the network1306. Then, a review is started using the received result of detection.In this event, the particles which require countermeasures arepreferentially reviewed, using the information added by the particleinspection apparatus 1301, thereby making it possible to rapidly analyzeparticles which can cause a failure. Similarly, the analyzer 1305 canalso analyze preferentially the particles which require countermeasuresbased on the information added by the particle inspection apparatus1301, thereby making it possible to rapidly advance an analysis on thecause of a failure.

These review data and result of analysis may be accumulated in the dataserver 1302, such that they are matched with results of testing in theelectric testing apparatus 1304 to confirm whether or not a failure iseventually determined. If a failure is not eventually identified, thedata server 1302 transmits data for changing the criteria for selectingparticles which require countermeasures to the particle inspectionapparatus 1301, so that the particle inspection apparatus 1301 changesthe criteria for determining whether or not countermeasures arerequired, thereby making it possible to more accurately select particleswhich require countermeasures and to readily take appropriatecountermeasures to a failure in the semi-conductor manufacturingprocess.

While the foregoing description has been made for an example in whichdata is transmitted and received through a network, thetransmission/reception of data need not be performed through a network,but data may be delivered through a removable recording medium or sheetsof paper on which data are printed out.

Next described will be another manner of using the particle inspectionapparatus 1301 according to the present invention in combination of thereview apparatus 1303. FIG. 16 shows a portion of FIG. 2 extractedtherefrom. In FIG. 16, an inspection apparatus 1601 is, for example, theapparatus for inspecting particles and/or defects of the presentinvention, and a review apparatus 1602, for example, a measuring SEM,reviews particles and/or defects on an object under inspection. Also, anetwork 1603 transmits/receives data between the inspection apparatus1601 and the review apparatus 1602, and is implemented, for example, bya system connected through the Ethernet. Next, the operation will bedescribed. It should be noted that in the following description,particles are taken as an example.

First, the inspection apparatus 1601 inspects particles on an objectunder inspection, and adds, for example, serial numbers allocated toparticles when they are detected, information on positions of particles,and information on sizes of particles to the result of inspection. Theresultant inspection data is transmitted to the review apparatus 1602through the network 1603. After the object under inspection is conveyedto the review apparatus 1602, the particles are reviewed in the reviewapparatus 1602. In this event, a scaling factor for reviewing in thereview apparatus may be adjusted in accordance with the information onthe particle sizes measured by the inspection apparatus 1602 to performan efficient reviewing operation. Specifically, when the particle sizeinformation acquired from the inspection apparatus 1601 shows a smallparticle, this particle is reviewed at a high scaling factor, so thatdetails on the small particle can be rapidly observed. On the otherhand, if the particle size information indicates a large particle, thisparticle is reviewed at a low scaling factor, so that the large particlecan be reviewed without extending off a review screen, thereby making itpossible to rapidly observe an entire image of the particle. Forexample, when the inspection data transmitted from the inspectionapparatus 1601 indicates a particle, the size of which is 0.1 μm, thisparticle is reviewed by adjusting the scaling factor such that thereview apparatus 1601 covers a field of view which spans 1 μm. On theother hand, when a particle has a size of 10 μm, the scaling factor isadjusted such that the review apparatus 1601 covers a field of viewwhich spans 100 μm. In this way, the review apparatus 1602 allows theuser to efficiently review small particles to large particles to rapidlyanalyze detected particles.

In this embodiment, description was directed to the case where particlesize information is supplied from the inspection apparatus 1601 tochange the scaling factor of the reviewing apparatus. As an alternativemethod, the scaling factor of the review apparatus 1602 and informationon the field of view may also be added to the inspection data. In thisembodiment, though a reviewing operation at scaling of ×100 on particlesby the reviewing apparatus 1602 was described, other scaling factor mayalso be employed. Further, if the accuracy of position information onthe particles by the inspection apparatus 1601 is known, the reviewingoperation may also be performed at a scaling factor determined both bythe factor based on the particle size information and the accuracy ofthe position information.

In this embodiment, though description was made where the lengthmeasuring SEM was employed as the reviewing apparatus, a reviewing SEMor an optical microscope system may also be employed. This technique canbe applied to any apparatus for reviewing or any function of reviewing.

This embodiment has been described for an example in which particle sizeinformation is outputted from the inspection apparatus 1601, and thescaling factor is adjusted in accordance with the size information inthe review apparatus 1602. As an alternative method, information on thereview scaling factor and the field of view for reviewing in the reviewapparatus 1602 may be added to the inspection data.

Also, this embodiment has been described for an example in which aparticle is reviewed in the field of view which spans an area ten timeswider than the size of the particle by adjusting the review scalingfactor for the review apparatus 1602. However, the scaling factor may beany other value. Also, if the accuracy of particle position informationis known in the inspection apparatus 1601, a particle may be reviewed ata scaling factor based on the particle size information in considerationof the accuracy of the position information.

Further, while this embodiment has been described for an example inwhich a particle is reviewed by the review apparatus 1602, the foregoingapproach may be applied when a particle is reviewed by the apparatus forinspecting particles and/or defects of the present invention.

Measurement of Size of Particle

Next, description will be made on the processing for measuring the sizeof a particle using the method and apparatus for inspecting particlesand/or defects according to the present invention.

FIGS. 3A, 3B are a diagram showing image data when a particle exists,and a diagram showing a distribution of intensity when particle data ismeasured.

FIGS. 4A to 4C are diagrams for comparing distributions of two types ofintensitys, and an explanatory diagram for showing how a maximum iscalculated for the intensity.

FIG. 3A shows an example of image processed by the signal processingcircuit 105 when a particle exists, where particle data 201 can be seenin a central portion of the image. The particle data 201 is outputtedfrom the light detector unit 104, and captured by the signal processingcircuit 105 as data having a contrast value. FIG. 3B shows FIG. 3A in athree-dimensional representation, where x- and y-axes are coordinateaxes for determining a position within the image, and z-axis representsthe intensity. Intensitys are plotted at corresponding positions, andconnected by lines. In FIG. 3B, a waveform 202 indicates waveform dataof the particle data 201. This waveform 202 can be approximated to aGaussian distribution from the nature of the illumination optical system101 and the detection optical system 103, and the width and height ofthe Gaussian distribution vary depending on the size of a particle onthe object under inspection 102. Further, the width and height of thedistribution also vary depending on the intensity of the laserillumination used in the illumination optical system 101. Therefore, theshape of a distribution and the amount of feature may have beenpreviously measured for a variety of standard particles using theinspection apparatus of the present invention configured as describedabove, such that the detected waveform 202 is compared with the resultsof measurements made on the standard particles to acquire information onthe size of the detected particle.

A method of comparing the waveform 202 of the particle with thewaveforms of the standard particles may involve previously measuring thetotal sum (integral) of the intensitys in the region occupied by theparticle data 201, i.e., data on the volume of the waveform 202, andcomparing the volume data of the particle data 201 with the volume dataof the standard particles. However, if the illumination optical system101 differs in intensity when the standard particles are measured andwhen particles on the object under inspection are measured, therespective volume data are divided by the intensities of theillumination optical system 101 for normalization, or the volume data ofthe particle data 201 or the standard particles is multiplied by theratio of intensities to correct the volume data.

As an alternative method of comparing waveforms, a maximum intensityvalue in the waveform 202 or the width of the waveform 202 may becompared.

Further, in addition to the volume data, the number of pixels on theimages of signals indicating the standard particles and particles mayalso be employed. This method will be described with reference to FIGS.42A and 42B. Like FIG. 3A, FIG. 42A shows the image of a particle, andparticle data 4201 represents the signal of the particle obtained fromlight reflected from the particle. FIG. 42B is a diagram showingcontrast values of the particle data 4201, and a particle signal portion4202 represents the signal of the particle. Referring to FIGS. 42A and42B, the volume data is the total sum of the contrast values ofrespectivverticalxels, so that the value of the volume data is 527.Further, the number of thverticalxels on the image is the number ofthverticalxels within the particle signal portion 4202. Thus, the numberof thverticalxels on the image is 14 pixels, and the width of the signalis 5 pixels in the x direction and 5 pixels in the y direction.

A method of calculating a maximum intensity value will be explained withreference to FIGS. 4A to 4C. FIGS. 4A, 4B show exemplary waveforms ofparticle data, similar to the waveform 202. Specifically, FIG. 4A showsan example in which a signal waveform of particle data acquired by thelight detector unit 104 is in the shape of pinnacle having a peak,indicating that the signal does not reach a saturation region of thelight detector unit 104. FIG. 4B in turn shows an exemplary signalwaveform of particle data which presents a plateau shape at the peak,indicating that the signal reaches the saturation region of the lightdetector unit 104 and does not include data exceeding the saturationregion.

The maximum intensity value is defined as the value which is determinedas maximum as a result of comparison between intensitys atrespectivverticalxels of the waveform, when particle data draws a signalwaveform as shown in FIG. 4A, i.e., a intensity at the peak point 301.On the other hand, when particle data draws a signal waveform as shownin FIG. 4B, a calculation is performed as described below to find amaximum intensity value.

First, in the saturation region 302, maximum lengths of the saturationregion are calculated in the x- and y-directions, respectively. FIG. 4Cshows a cross-section of FIG. 4B taken along the maximum length region.In FIG. 4C, the horizontal axis is a coordinate axis representing theposition in the maximum length region, while the vertical axis is acoordinate axis representing the intensity. The intensity 303 indicatesthe saturation level of the light detector unit 104. On thiscross-section, three or more unsaturated signals 304 are selected. Here,description is made on the assumption that three points are selected. Aspoints to be selected, three points having the largest intensitys areselected from unsaturated signals on the cross-section. Assuming thatthe three points are at coordinates x1, x2, x3, and have intensitys z1,z2, z3, respectively, equations representing Gaussian distributions arederived using unknown numbers k, σ, u:z1=k/σ·exp(−(x1−u)²/(2·σ²))z2=k/σ·exp(−(x2−u)²/(2·σ²))z3=k/σ·exp(−(x3−u)²/(2·σ²))The unknown values k, σ, u can be found by solving the simultaneousequations. Then, the maximum intensity value in FIG. 3B can becalculated using the resulting values of k, σ as follows:k/σ

It should be noted that although the example shown herein uses theunknown value u for calculating the maximum intensity value, the unknownvalue u need not be used. In this case, two points are selected from theunsaturated signals 304. Selected signal points are those having thelargest intensitys from unsaturated signals on the cross-section.Assuming that the two points are at coordinates x1, x2, and haveintensitys z1, z2, respectively, equations representing Gaussiandistributions are derived using unknown numbers k, σ:z1=k/σ·exp(−(x1)²/(2·σ²))z2=k/σ·exp(−(x2)²/(2·σ²))

Since the unknown values k, σ can be found by solving the simultaneousequations, the maximum intensity value in FIG. 3B can be calculatedusing the values of k, σ as follows:k/σ

A particle size can be measured by comparing the maximum intensity valuederived from the foregoing calculation for a detected particle withthose for the standard particles.

Next, another embodiment for calculating the maximum intensity valuewill be described with reference to FIG. 17.

FIG. 17A to 17C are a graph showing a signal distribution of particledata which presents a plateau shape at the peak; a diagram showing theshape of the saturated signal portion; and an explanatory diagram forexplaining how the maximum intensity value is calculated. FIG. 17A showsthe relationship between a signal waveform 1701 and a peak region 1702,wherein the peak region 1702 in the signal waveform 1701 does notinclude data exceeding the saturated level since the peak region 1702reaches the saturation region of the light detector unit 104. FIG. 17Bshows a cross-section of the signal waveform 1701, where the verticalaxis represents the intensity, and the horizontal axis representsthverticalxel position in the signal. In FIG. 17B, a saturation level1703 indicates the saturation level of the light detector unit 104, anda signal width 1704 indicates the width of the peak region 1702. Also, aintensity 1705 is a maximum intensity value which is generated when anunsaturable detector is used for the light detector unit 104.

Next explained is a method of calculating the maximum intensity value1705 from the saturated signal waveform 1701. Assuming that thesaturation level 1703 is represented by SL; the signal width 1704 by SW,and the intensity 1705 by PL, the illustrated waveform is approximatedto a Gaussian distribution to derive the following equations:SL=k/σ·exp(−(−SW/2)²/(2·σ²))PL=k/σwhere k is a coefficient, and σ is a value calculated from theconfiguration of the optical system in the apparatus for inspectingparticles and defects of the present invention.

Therefore, from the two equations, PL is calculated as follows:PL=SL/exp(−(−SW/2)²/(2·σ²))Here, since SL indicates the output of the light detector unit 104 whenit is saturated, SL represents 255 gradation levels when an A/Dconverter of the light detector unit 104 has a 8-bit resolution. σ isgiven a value from zero to one depending on the configuration of theoptical system. Next, a method of calculating SW will be described. FIG.17C shows the shape of the peak region 1702, in other words, a region inwhich the light detector unit 104 is saturated. FIG. 17C includes asaturation region 1706 and a signal width 1704. Since the signalwaveform 1701 is regarded as a Gaussian distribution, the saturationregion 1706 can be assumed to be circular. Therefore, assuming that thesignal width 1704 is represented by SW, and the saturation region 1706by SA, SW is calculated by:SW=2·√{square root over (SA/π))}In the above equation, √(A) represents a calculation of a square root ofA, and π is the Ludolphian number. The saturation region 1706 may becomprised of the number of pixels in which the light detector unit 104is saturated. Here, a saturated pixel may be represented by a maximum ofthe output from the A/D converter of the light detector unit 104, andmay be set in consideration of electric noise in the light detector unit104. For example, when the A/D converter has an 8-bit resolution, theoutput represents a maximum of 255 gradation levels. It may be thoughtthat the output at 245th gradational level or higher is saturated ifelectric noise accounts for 10 gradation levels.

If the signal waveform 1701 is not saturated, a similar calculation maybe performed using a maximum of the signal waveform 1701 as thesaturation level 1703.

Since the maximum intensity value can be calculated from the foregoingprocess, the size of a detected particle can be measured by comparingthe values calculated using the standard particles with a valuecalculated using the detected particle.

While the foregoing description has been made for the maximum intensityvalue as an example, the integral of intensity over particle data may beused instead of the maximum intensity value. In this case, the integralof intensity over particle data may be calculated by adding contrastvalues of respectivverticalxels in the detected particle signal. Theadvantage of using the integral is to allow reduction in the samplingerror of a signal.

A method of correcting intensity when the integral of intensity isemployed will be described. FIG. 45 is a diagram showing athree-dimensional representation of the Gaussian distribution. FIG. 45is the case where the signal is saturated when Y=Y₀. The method to bedescribed below is the one for calculating the intensity of the entireGaussian distribution when the intensity of a V3 portion, or a portionbelow a line indicating Y=Y₀ in FIG. 45 is obtained.

First, assume that the total volume of the entire Gaussian distributionis represented by V1 in FIG. 45, the volumes above and below the lineindicating Y=Y₀ are represented by V2, and V3, respectively. Then, alsoassume that the shape of a section through the X axis of the Gaussiandistribution in FIG. 45 is obtained from:Y=exp(−X2/2/σ²)At this point, through integration with respect to the Y axis, V1 isexpressed by:V1=2·π·σ²Further, V2 is expressed by:V2=2·π·σ²(Y0·Log (Y0)+1−Y0).“Log” in the above equation indicates calculation of the naturallogarithm. If a volume ratio V1/V3 is expressed as CC, CC can becalculated from:CC=V1/(V1−V2).Thus, using the above equation, CC is calculated from:CC=1/(Y0·(1−Log (Y0))).Since Y0=exp(−SW²/2/σ²), CC can be expressed as:CC=1/exp(−SW ²/2/σ²)/(1+SW ²/2/σ²).Accordingly, if the obtained intensity is V3, the entire intensity V1can be calculated from:V1=V3·1/exp(−SW ²/2/σ²)/(1+SW ²/2/σ²).Correction of the intensity can be thereby performed.

Also, while the foregoing embodiment employs an 8-bit A/D converter, anA/D converter having 10 bits or more may be used. Use of the A/Dconverter having a lot of bits is advantageous in that it can capture aslight change in the intensity of light received at the light detectorunit. Thus, more accurate calculation of the size of a particle and/or adefect can be thereby performed. Further, while the foregoing embodimenthas been described for an example of calculating the signal width 1704as the diameter of a circle, a width of the saturation region whichindicates a maximum length or a minimum length may be used instead ofthe diameter.

In the description on the configuration of the apparatus, theillumination optical system 101 uses laser light as an example in theforegoing embodiment. Alternatively, white light may be used instead oflaser light. Also, when an object under testing has repeated circuitpatterns, the foregoing measurement of the size may be made after takinga difference between an image of the repeated pattern on which noparticle exists and an image of the same on which a particle exists.Also, irrespective of the presence or absence of repeated patterns, ifdata on scattered light or data on reflectivity associated with thecircuit pattern or a film, for example, an oxide film or a metal film,can be acquired beforehand, such data may be used to correct data on thesize of a particle on the circuit pattern or the film. Furthermore,while the foregoing embodiment measures the particle size by comparingit with the sizes of standard particles, the size of the particle may becompared with a particle, the size of which is known, instead of thestandard particles.

Next, an exemplary method of calculating a particle size from themaximum intensity value will be described with reference to FIG. 15 whenusing data on a particle, the size of which is known. FIG. 15 is a graphin which the horizontal axis represents a maximum intensity value ofparticle acquired from the apparatus for inspecting particles and/ordefects according to the present invention, and the vertical axisrepresents the particle size. Here, the maximum intensity values ofparticles are calculated by the aforementioned method, while the size ofa particle is derived by measuring a horizontal dimension and a verticaldimension of the particle using a review apparatus such as a measuringSEM, multiplying the horizontal dimension by the vertical dimension, andtaking a square root of the product. In FIG. 15, a plot point 1501indicates data on a particle, so that FIG. 15 indicates data on aplurality of particles. An approximate curve 1502 is calculated by aleast-square method based on the data at the plot points 1501. In thisevent, the approximate curve can be expressed by an equation y=a·x+bwhen the horizontal axis of the graph is represented by x, and thevertical axis of the same by y, where, a and b are values found by aleast-square method.

For calculating a particle size from a maximum intensity value, arelational expression between the maximum intensity value and theparticle size is found and is used to calculate the particle size fromthe maximum intensity value.

Next, the operation will be described. First, the approximate curve 1502has been previously calculated by the aforementioned method. Next, anobject under inspection is inspected using the apparatus for inspectingparticles and/or defects according to the present invention. Then, amaximum intensity value for the particle is calculated as describedabove during the inspection. In this event, using the approximate curve,the maximum intensity value is substituted into x of the approximatecurve to calculate y which is determined as the particle size.

Examples of the results calculated by the foregoing method are shown inFIGS. 30A, 30B and 31. FIGS. 30A, 30B are graphs, wherein the horizontalaxis represents the particle size calculated from signal outputted fromthe apparatus for inspecting particles and/or defects according to thepresent invention, and the vertical axis represents the particle sizemeasured by a measuring SEM. A plot point 3101 corresponds toinformation on one particle. A straight line 3102 in turn represents anapproximate line when each of plot points 3101 is least-mean-squareapproximated, and a value 3103 indicates a correlation value at the plotpoint 3101.

Further, FIG. 30A shows the result of measuring sizes of particlesdetected on a wafer having a one-layer pattern, and FIG. 30B shows, byway of example, the result of measuring sizes of particles detected on awafer having a multi-layer pattern.

FIG. 31 shows, by way of example, SEM photographs of used particles inaddition to the particle sizes calculated from signals outputted fromthe apparatus for inspecting particles and/or defects according to thepresent invention on the horizontal axis, and the particle sizesmeasured by the measuring SEM on the vertical axis, in a manner similarto FIGS. 30A, 30B.

While this embodiment calculates a square root of the vertical dimensionand the horizontal dimension of each particle, the size of a particlemay be defined as the larger one of the vertical dimension and thehorizontal dimension of the particle, or an average value of thevertical dimension and the horizontal dimension of the particle.Alternatively, the major axis of a particle may be used, or the minoraxis of the particle may be used. Further, the approximate curve may bea first-order curve, i.e., a straight line, or a higher-order curve, alogarithmic curve or an exponential curve, or a combination of aplurality of curves.

If the provision of different approximate curves for respective shapesof particles results in a better correlation of the particle sizescalculated as described above to the particle sizes measured using themeasuring SEM, a different approximate curve may be used for each shapeof particle. Here, the difference in the shape of a particle refers to,for example, the difference between a spherical particle and a flatplate-shaped particle, or the difference between a particle and ascratch, when the difference lies in the ratio of the particle sizemeasured from above to the particle size measured from the side.

Now, a method of distinguishing a particle from a scratch will bedescribed with reference to FIGS. 18A, 18B. FIG. 18A illustrates theconfiguration for discriminating between a particle and a scratch, andFIG. 18B shows how they are discriminated. FIG. 18A comprises asubstrate 1801; a particle 1802; vertical-illumination light 1803 whichilluminates the substrate from a perpendicular direction; obliqueillumination light 1804; a light detector 1805; a storage circuit 1806;and a comparator circuit 1807. In the illustrated configuration, thevertical-illumination light 1803 is emitted to the substrate at an angleclose to a direction perpendicular to the surface of the substrate 1801,while the oblique illumination light 1804 is emitted to the substrate1801 at an angle close to a direction horizontal to the substrate 1801.Their light sources may be an Ar laser, a YAG laser, or the like, by wayof example. The light detector 1805, in turn, may be a TV camera, a CCDlinear sensor, a TDI sensor, or a photomultiplier.

Next, the operation will be described. A particle or a scratch isirradiated with the vertical-illumination light 1803 to detect scatteredlight from the particle or scratch by the light detector 1805. Theamount of scattered light is stored in the storage circuit 1806.Subsequently, the irradiation of the vertical-illumination light 1803 isstopped, and the oblique illumination light 1804 is irradiated to theparticle or scratch to detect scattered light from the particle orscratch by the light detector 1805. The amount of scattered light isstored in the storage circuit 1806. Next, the light intensities, or theamounts of scattered light stored in the storage circuit 1806 arecompared by the comparator circuit 1807. The comparator circuit 1807calculates the ratio of the amount of scattered light when thevertical-illumination light 1803 is irradiated to the amount ofscattered light when the oblique illumination light 1804 is irradiated,and compares the ratio with a previously determined threshold todetermine a particle or a scratch. A determination method used hereinmay take advantage of the fact that a particle has a smaller ratio ofthe amounts of scattered light, and a scratch has a larger ratio, asshown in FIG. 18B.

Next, a method of setting the threshold for discriminating between aparticle and a scratch will be described. FIG. 46A is a graph in whichthe amount of scattered light caused by the vertical-illumination lightis plotted on the horizontal axis and the amount of scattered lightcaused by the oblique illumination light is plotted on the verticalaxis. In this embodiment, discrimination between a particle and ascratch is made in advance, and a particle is indicated by ∘, while ascratch is indicated by ▴. Next, by adding to FIG. 46A a discriminationline 4601 for discriminating between a particle and a scratch, FIG. 46Bis obtained. This discrimination line 4601 represents thresholds fordiscriminating between particles and scratches. Incidentally, thediscrimination line 4601 may be arbitrarily set by the operator, or maybe automatically calculated. Automatic calculation of the discriminationline 4601 is advantageous in that, even if different operators performthe setting operation, the same threshold can be set.

Next, a method of automatically calculating the discrimination thresholdwill be described with reference to FIG. 46C. First, an approximate line4602 is calculated from particle data. This approximate line 4602 isexpressed by:Y=a·X+b,In the above equation, X represents the horizontal axis of the graph,while Y represents the vertical axis of the graph, and a and b arevalues obtained through the least-square method. Next, an approximateline 4603 is calculated from scratch data. As in the case of using theparticle data, the approximate line 4603 is expressed by:Y=c·X+dwhere c and d are values obtained through the least-square method.Then, the discrimination threshold should be calculated from anintermediate line 4604 between the two approximate lines from:Y=((a+c)/2)·X+((b+d)/2)

In this embodiment, though a linear threshold is taken as an example ofthe discrimination threshold, a curvilinear threshold may also beemployed, and a plurality of curves may be combined for calculating thediscrimination threshold. Further, suppose that three or more types ofobjects are present for inspection. When discrimination among aparticle, a scratch, and a pattern defect are to be made, for example inthis case, a plurality of thresholds should be set for discrimination.Further, in this embodiment, though the case where two characteristicamounts, or the amount of scattered light caused by thevertical-illumination light and the amount of scattered light caused bythe oblique illumination light are used for determination was described,the characteristic amount other than the amount of scattered light mayalso be used. If three or more characteristic amounts are obtained, aplurality of graphs may be employed for determination, as shown in FIGS.47A and 47B. As shown in FIGS. 47A and 47B, by additionally displaying acorrect answering rate 4701 for discrimination in each of the graphs,the performance of the applied discrimination threshold may also bedisplayed.

In this embodiment, description was directed to an example where theresult of determination by the review apparatus in advance is employed.However, if the discrimination threshold can be calculated from a pastexample in advance, the past example may also be used for determination.

Next, a method of calculating a particle size when there are a pluralityof approximate curves will be described with reference to FIG. 19. FIG.19 comprises a storage unit 1901 for storing a maximum of detectedsignals; a discrimination unit 1902 for discriminating between aparticle and a scratch; a conversion curve selection unit 1903; and aparticle size calculation unit 1904.

Next, the operation will be described. First, a conversion equation forcalculating a particle size from a maximum intensity value using theaforementioned method has been created for each of a particle and ascratch in the apparatus of inspecting particles and/or defectsaccording to the present invention and stored in the conversion curveselection unit 1903. Next, a wafer is inspected by the inspectionapparatus. In this event, a maximum intensity value of a detectedsubstance is stored in the storage unit 1901. Next, the discriminationunit 1902 determines whether the detected substance is a particle or ascratch by the aforementioned method. Based on this determination, aconversion curve is selected from the conversion curve selection unit1903, and the selected conversion curve and the maximum intensity valuestored in the storage unit 1901 are inputted to the particle sizecalculation unit 1904 to calculate the size of the particle.

Details of the method of creating a conversion curve will be describedwith reference to FIGS. 48A and 48B. First, data on the amount ofscattered light detected from a detected substance by the apparatus forinspecting particles and/or defects according to the present inventionis stored. Then, the detected substance is reviewed by the reviewapparatus to determine whether the substance is a particle and/or adefect, and then the size of the detected substance is measured. Next, agraph where the intensity of the scattered light and the size of thedetected substance are plotted is created for each particle and eachdefect. FIGS. 48A and 48B are examples of the graphs thus created. FIG.48A is a graph created when the detected substance is a particle, andonly the particle data is plotted therein. The graph sets the amount ofscattered light from the particle on the horizontal axis and sets on thevertical axis the size of the particle measured by the review apparatus.Further, an approximate curve 4801 is the one calculated from the dataplotted in FIG. 48A, and is the straight line calculated through theleast-square method, for example. Likewise, FIG. 48B is a graph createdwhen the detected substance is a defect, and only the defect data isplotted therein. Further, an approximate curve 4802 is the onecalculated from the defect data, as in FIG. 48A.

If these approximate curves 4801 and 4802 calculated according to theabove-mentioned method are set as conversion lines, and if in thesubsequent inspection, the size of a particle and/or a defect iscalculated using the conversion curves set as described above, the sizeof the particle or the defect can be calculated with good accuracy.

While the foregoing embodiment has described for an example in which aconversion curve is set according to the shape of a particle and adefect, a different approximate curve may be used according to theposition on an object under inspection at which a particle is detected,for example, whether a particle on a circuit pattern or a particle on aregion without patterns. Alternatively, a different approximate curvemay be used depending on the surface state of an object underinspection, for example, whether the surface is coated with an aluminumfilm or a tungsten film.

[Method of Calibrating Measured Particle Size]

Next described will be a method of calibrating a particle size measuredby the apparatus for inspecting particles and/or defects according tothe present invention. This calibration may be used, for example, whenthe amount of illumination light has changed due to a deterioration inthe illumination optical system in the apparatus for inspectingparticles and/or defects according to the present invention.

An exemplary calibrating method will be described. First, mirror waferswith standard particles having known sizes attached thereto is preparedas calibration wafers. Two or more types of standard particles arepreferably prepared. For example, a standard particle of 0.2 μm and astandard particle of 0.6 μm are attached to mirror wafers, respectively.Next, these wafers are inspected by the apparatus for inspectingparticles and/or defects according to the present invention to displaythe sizes of detected particles. In this event, if the inspectionapparatus does not fail, peaks will appear at 0.2 μm and 0.6 μm on thescale of the histogram.

For example, FIG. 26 is a graph showing the number of detected particleson the vertical axis, and sizes of the detected particles on thehorizontal axis. As can be seen in FIG. 26, the number of detectedparticles is increased at 0.2 μm and 0.6 μm on the scale. In contrast toFIG. 26, FIG. 27 shows an example when the laser light source used inthe illumination optical system 101 has deteriorated to reduce theamount of illumination light to one half, wherein the number of detectedparticles is increased at 0.1 μm and 0.3 μm on the scale. In otherwords, FIG. 27 shows an example in which a reduced amount ofillumination light results in a less amount of scattered light, so thatparticle sizes are measured smaller than correct values.

Next explained will be a method of calculating a calibration coefficientfor calibrating the inspection apparatus. Assume first that the size ofthe standard particle inspected above is SS, and the size of a particlemeasured by the inspection apparatus of the present invention is IS. Inthis event, since a reduced amount of illumination light is calculatedfrom the ratio of SS to IS, the calibration coefficient, designated VR,is calculated by:VR=SS/ISTherefore, the calibration may be accomplished by increasing the amountof illumination light by a factor of VR or by multiplying a conversionequation for calculating the a particle size from the amount ofscattered light by VR. Specifically, in the aforementioned example,assuming that the size SS of the standard particle is 0.2 μm and thesize IS of the particle measured by the inspection apparatus is 0.1 μm,the calibration coefficient VR is calculated as:VR=2so that the amount of illumination light may be increased twice.

While the foregoing example has employed a wafer with a standardparticle of a known size attached thereto as a calibration wafer, thecalibration wafer is only required to have a particle and/or a defect ofknown size attached thereto, so that a wafer having a defect of knownsize intentionally created therein may be used instead.

Next, another calibration method will be described with reference toFIG. 2.

This is a method which uses values measured by the review apparatus asparticle sizes. First, an inspection is made in the particle inspectionapparatus 1301, and information on selected particles is added to theresults of inspection by the particle inspection apparatus 1301, forexample, serial numbers allocated to particles when they were detected,information on the positions of the particles, information on the sizesof the particles, and so on, and transmitted to the data server 1302through the network 1306. After the wafer has been conveyed to thereview apparatus 1303, the wafer is reviewed by the review apparatus1303, and information on particle sizes measured therein is added to theinspection result. Here, the particle size information is derived, whenusing, for example, a measuring SEM as the review apparatus 1303, bymeasuring the horizontal dimension and vertical dimension of a particleusing the measuring SEM, multiplying the horizontal dimension by thevertical dimension, and taking a square root of the product. Next, theinformation added to the inspection result is transmitted to the dataserver 1302, and the added information is received by the particleinspection apparatus 1301 to calibrate the particle size informationoutputted from the particle inspection apparatus 1301 based on the sizeinformation.

The calibration method will be described with reference to FIG. 28. FIG.28 is a graph showing the information on the size of each particlemeasured by the particle inspection apparatus 1301 on the horizontalaxis, and the information on the size measured by the review apparatus1303 on the vertical axis. In FIG. 28, a plot point 2901 indicatesinformation on the size of the same particle, so that FIG. 28 plotsinformation on a plurality of particles. Here, if the particle sizes arecorrectly measured, plot points 2901 should be arranged along a straightline 2902. The calibration method first finds an approximate line forthe data of the plot points 2901 through a least-square method or thelike. This approximate line is the straight line 2903 which is expressedby an equation:y=a·x+bwhere x represents the particle size measured by the inspectionapparatus on the horizontal axis, and y represents the size of theparticle measured by the review apparatus 1303 on the vertical axis.Also, a and b are values found by a least-square method. Next, theparticle is inspected by the apparatus for inspecting particles and/ordefects according to the present invention, the size of the particle ismeasured, and the measured size is substituted into x in the aboveequation. The resulting value y is determined as the size of theparticle after calibration.

While the linear approximation has been described as the calibrationmethod, the approximation may be made to a higher order curve, alogarithmic curve, an exponential curve, or a combination of curves. Inaddition, a wafer for use in calibrating the particle size is notlimited to one, but a plurality of wafers may be used.

In the foregoing description, particles are inspected using scatteredlight. This method is advantageous in that particles can be efficientlyfound. Also advantageously, when particle sizes are calculated by theaforementioned method, particles can be found without requiring aspecial light source for measuring the sizes, and measurements of thesizes can be made with scattered light from the same light source.

Analysis on Cause of Failure and Display of Result

Next, description will be made on a procedure for analyzing a cause offailure and a procedure for displaying the result of analysis to theuser when particle sizes are measured using the apparatus for inspectingparticles and/or defects according to the present invention.

FIGS. 5A to 5C are diagrams showing that the relationship betweenparticle sizes and the number of detected particles changes due to acause of failure.

FIG. 6 is a line graph showing the number of detected particles andparticle sizes.

FIG. 7 is a histogram showing the number of detected particles andparticle sizes.

FIGS. 8A, 8B are schematic diagrams each clearly showing particles of aparticular size on a wafer;

FIGS. 9A to 9C are graphs each showing a transition of the number ofdetected particles for each particular size.

FIG. 10 is a diagram illustrating a screen for displaying to the user acause by which particles are generated.

FIG. 20 is a histogram showing the number of detected particles and theparticle sizes on a plurality of wafers.

FIG. 21 is another histogram separately showing detected particles andscratches on a wafer.

One important idea of the present invention is to use particle sizeinformation for analyzing a cause of failure. The following descriptionwill be made on the effectiveness of using the particle size informationfor analyzing a cause of failure.

Assume herein that particles have been detected from a wafer processedby a semiconductor manufacturing apparatus, for example, an etchingapparatus, and the relationship between particle sizes and the number ofdetected particles are as shown in FIGS. 5A to 5C. A region 401 in FIG.5A shows a distribution of particles steadily generated in a process ofan etching apparatus. In this case, the particle sizes concentrate in arange from a to b, so that a gently-sloping mountain is formed.

On the other hand, FIG. 5B shows an exemplary distribution of particleswhich are generated when the apparatus is faulty. In this case, largeparticles (a range of sizes larger than c) are frequently generated asshown in a region 402, in addition to the particles in the steady stateshown in the region 401. It is contemplated that the cause for suchlarge particles is deposits on the inner wall surface of the etchingapparatus are peeled off the wall surface during the etching process.FIG. 5C also shows an exemplary distribution of particles which aregenerated when a failure occurs. In this case, FIG. 5C shows thatparticle sizes also concentrate in a range from d to e in addition tothe particles in the steady state. It is contemplated that the cause forsuch particles is particular patterns which are peeled off and dispersedduring the etching process.

As described above, in manufacturing apparatuses for semiconductor orthe like, there is a relationship between the sizes of generatedparticles and the cause by which the particles are generated, so thatthe cause for particles generated in a certain manufacturing apparatuscan be immediately known by managing the generation of particles ofparticular sizes. In other words, by investigating the relationshipbetween the size of particles and the number of generated particles, thecause of failure can be revealed.

It should be understood that the values a-e of course depend onparticular manufacturing apparatuses, manufacturing processes and so on.Also, particles generated by a different cause may exhibit a differentdistribution of size, so that it is preferred to prepare data whichconforms to a particle size distribution for each cause. In addition,while this embodiment intends to identify the cause for generatedparticles in two ranges, the range of particle size may be divided intomore than two ranges.

Next, description will be made on a specific function of analyzing acause of failure.

First described is how the particle sizes and the number of detectedparticles are displayed on the data display unit 106. The data displayunit 106 displays a graph showing a particle size distribution asdescribed above, i.e., a graph which allows the user to understand therelationship between particle sizes and the number of detectedparticles. FIG. 6 is a graph showing the particle size on the horizontalaxis and the number of detected particles on the vertical axis. A point501 indicates the number of detected particles of certain size. In thisexemplary graph, data on the number of detected particles is provided inincrements of 0.1 μm. A curve 502 is a line connecting the points 501.By displaying the graph as in this embodiment, it can be immediatelyseen how particles detected from an object under inspection 102 aredistributed.

In the graph of FIG. 6, a minimum value on the horizontal axis may be aminimal detectable dimension of the particle inspection apparatus, or aparticle size which should be managed on a semiconductor manufacturingline.

The particle size which should be managed on the semiconductormanufacturing line is hereinafter referred to as a management particlesize.

Also, the scale may be represented in a logarithmic or linear form. Theunit of scale may be variable. Further, a displayed range of each axismay be fixed or variable. For example, particles generated by aparticular cause alone may be displayed by displaying particles of aparticular size. The contents represented on the vertical axis and thehorizontal axis may be replaced with each other. Instead of the numberof detected particles, the density of particles may be shown. Further,while this embodiment displays a graph, an average value of the graph,and a standard deviation or variance of the graph may also be displayedother than the graph. Also, while this embodiment displays particle dataon one wafer as one graph, the graph need not be displayed for only onewafer. An average value, a standard deviation and a variance of particledata on a plurality of wafers may be displayed, and particle data on aplurality of wafers may be displayed side by side.

The graph may be displayed in histogram as shown in FIGS. 7 and 32. Thegraphs on these figures indicate the particle size on the horizontalaxis, and the number of detected particles on the vertical axis,similarly to FIG. 6. These graphs display the particle size on thehorizontal line divided into certain sections. FIG. 7 shows datasections in increments of 0.2 μm. FIG. 32 in turn shows data sections inincrements of 0.1 μm, wherein particles having the size equal to or morethan 5 μm are counted in a bar graph 3301, and a histogram for particleshaving the size smaller than 1.1 μm and a histogram for particles havingthe size equal to or larger than 1.1 μm are displayed in differentcolors, by way of example. In addition, a function may be added fordisplaying information on the positions of a detected particles in aselected portion of a bar graph. Also, a review image may be displayedfor the detected particles in the selected portion.

FIG. 34 shows another example of graphical representation. FIG. 34 showsan example in which the particle size is set on the horizontal axis, andan accumulated number of particles is set on the vertical axis. Here,the accumulated number refers to the number of detected particles of acertain size or larger.

FIG. 35 shows a further example of graphical representation. FIG. 35shows an example in which the particle size is set on the horizontalaxis, and the number of detected particles is set on the vertical axis,with a curve 3601 indicative of the number of detected particles, and anequation expressing the curve 3601 indicative of the number of detectedparticles additionally indicated in the graph. In the equation 3601, xrepresents the particle size, and y the number of detected particles.The equation 3602 is an approximate equation derived from the number ofdetected particles for each particle size. The curve 3601 represents theequation 3602.

FIG. 36 shows a further example of graphical representation. FIG. 36 isthe graph which sets the particle size on the horizontal axis, and setsthe detected particle quantity rate on the vertical axis, with abroken-line graph 3501 indicative of the detected particle quantity rateand a particle size 3502 indicative of the particle size with themaximum particle quantity rate additionally indicated in the graph. Thedetected particle quantity rate is the proportion of the number ofdetected particles for each size to the total number of the particlesdetected by inspection.

FIG. 37 shows a still another example of graphical representation. FIG.37 sets the particle size on the horizontal axis, and sets theaccumulated number of particles on the vertical axis, with a curve 3701indicative of the accumulated number of particles, a straight line 3702indicative of the position of the management particle size on thesemiconductor device manufacturing line, and a value 3703 of themanagement particle size, additionally indicated in the graph. Theaccumulated number of particles is herein defined as the total number ofparticles of each size or smaller.

FIG. 38 shows a still further example of graphical representation. FIG.38 sets the particle size on the horizontal axis, and the accumulatedparticle quantity ratio on the vertical axis on the vertical axis, witha curve 3801 indicative of the accumulated particle quantity ratio,particle quantity ratios 3802 and 3803 in regard to the particles ofcertain sizes or larger, additionally indicated in the graph. Theaccumulated particle quantity ratio is herein defined as the ratio ofthe number of particles of each size or smaller to the total number ofparticles detected by inspection. Further, the particle quantity ratios3802 and 3803 are the ratios of the number of particles of certain sizesor larger to the total number of particles detected by inspection. Theparticle quantity ratio 3802 indicates that the ratio of particles of0.5 μm or larger to the total number of detected particles is one, orindicates that all the detected particles are 0.5 μm or larger in size.The particle quantity ratio 3803 indicates that the ratio of particlesof 1.0 μm or larger to the total number of detected particles is 0.45,or indicates that 45% of all the detected particles are the ones of 1.0μm or larger.

FIG. 39 shows a still further example of graphical representation. FIG.39 sets the particle size on the horizontal axis, and sets the number ofparticles of respective sizes on the vertical axis. The horizontal axisis represented in a logarithmic form.

FIG. 40 shows a still further example of graphical representation. FIG.40 sets the particle size on the horizontal axis, and sets the number ofparticles of respective particle sizes on the vertical axis, with aparticle count distribution 4001 and an average particle countdistribution 4002 additionally indicated in the graph. The particlecount distribution 4001 is the distribution of the number of particlesdetected by a single inspection, while the average particle countdistribution 4002 is the average value of the number of particlesdetected when other wafers have also been inspected.

FIG. 20 shows a further example of graphical representation. While theexample in FIG. 7 displays data for one wafer, data on a plurality ofwafers may be displayed side by side as shown in FIG. 20. Specifically,FIG. 20 is an example in which the number of detected particle is set onone of three coordinate axes; the particle size on another axis; and thewafer number on the remaining axis. In this example, data sections forthe particle size are set in increments of 0.1 μm from zero to 1 μm,particles having sizes equal to or larger than 1 μm are counted on thesame bar graph, and the total number of detected particles is alsodisplayed in the graph. As is the case with FIG. 6, an average value,standard deviation and variance may also be displayed on the graph ofFIG. 20.

FIG. 21 shows a further example of graphic representation. FIG. 21 showsan example in which displayed data are classified into particles andscratches and also classified by size.

Though the above descriptions were directed to the graphs showing therelationships between the size of particles and the number of detectedparticles, the contents of display desired to be used for a certaindiagram may also be employed, in combination with the contents ofdisplay for other diagram.

Next, description will be made on a function of displaying informationon the positions of detected particles. FIG. 8A shows information on thepositions of all particles detected by a particle inspection.

In FIG. 8A, detected particles 702 exist within a contour 701 of an8-inch semiconductor wafer. In this event, as a mouse is click once ortwice on a bar graph 601 in FIG. 7, the section of the bar graph 601,i.e., displayed particles 703 of sizes ranging from 2.8 μm to 3.0 μm inFIG. 8A are changed as shown in FIG. 8B. The inspection apparatus hassuch a function so that the user can immediately find the positions onan object under inspection 102 of particles having sizes in a particularrange.

FIG. 22 shows an exemplary result of a particle inspection displayedafter the inspection. The display in FIG. 22 comprises an inspection map2201 indicative of the positions at which particles are detected; ahistogram 2202 for the sizes of the detected particles; a review button203; a review image 2204 of the detected particles; particles 2205; aparticle size data section 2206 to be reviewed. The review image 2204 isdisplayed centered at the particle 2205. In this example, particleshaving sizes ranging from 2.8 μm to 3.0 μm in the data section 2206 areselected.

In operation, after particles are inspected by the apparatus forinspecting particles and/or defects according to the present invention,the inspection map 2201 is displayed as information on the positions ofthe particles, and the histogram 2202 is displayed as information onparticle sizes. Then, the data section 2206 is selected as a particlesize to be reviewed. Clicking on the review button 2203 causes thereview image 2204, provided by the apparatus for inspecting particlesand/or defects of the present invention, to be displayed. Here, thereview image 2204 may be an image generated from scattered laser light,or an image captured by a microscope. The positions of particlesdisplayed on the review image 2204 may also be additionally displayed onthe inspection map 2201, and the particle numbers assigned by theapparatus for inspecting particles and defects according to the presentinvention may also be displayed.

FIGS. 43A and 43B show another exemplary results of a particleinspection displayed after the inspection. FIGS. 43A and 43Brespectively comprise an inspection map 4301 indicative of the positionsat which particles are detected, a histogram 4302 for the sizes of thedetected particles, and a scroll bar 4303 that specifies the size of aparticle to be displayed. In this example, the scroll bar 4303 canadjust the size of particles ranging from 1.0 μm to 3.0 μm. FIG. 43Ashows the case where the button of the scroll bar 4303 is located at theleftmost position, while FIG. 43B shows the case where the button of thescroll bar 4303 is located at the position of 2.2 μm.

In operation, after particles are first inspected by the apparatus forinspecting particles and defects according to the present invention, theinspection map 4301 is displayed as information on the positions ofparticles, and the histogram is displayed as information on the sizes ofthe particles. The scroll bar 4303 is also displayed. This is the stateindicated in FIG. 43A. Then, in FIG. 43B, the size of a particle desiredto be displayed is set to 2.2 μm or larger. For setting, the button ofthe scroll bar 4303 should be shifted from the position in FIG. 43A tothe right by a mouse, to the position of 2.2 μm. At this point, displayof particles on the inspection map 4301 is changed according to theshift of the button of the scroll bar 4303. In the case of FIG. 43B, forexample, since the scroll bar 4301 is at the position of 2.2 μm, theinspection map 4301 shows particles of 2.2 μm or larger alone. At thesame time, in the histogram 4302 indicating the sizes of detectedparticles, the color of the particles of 2.2 μm or larger is made to bedifferent from the color of particles of less than 2.2 μm. As describedabove, by changing particles to be displayed, a distribution ofparticles of respective sizes can be quickly seen.

In this embodiment, though description was directed to the case whereonly the particles having sizes equal to or larger than a specified sizeare displayed on the inspection map 4301, display of only the particlesof less than the specified size may also be performed. If onlydiscrimination between the particles of sizes equal to or larger thanthe specified size and other particles can be performed, particles ofany size can be displayed. In order to perform discrimination, thecolor, form, and size of display should be changed, or a particle markshould be flashed, for example. If only the particles of the specifiedsize are displayed, it is easy to find where the particles of thespecified size are present. If other particles are also displayedtogether with the particles of the specified size, positionalrelationship of the particles of the specified size with respect to allthe particles can be easily comprehended. In the histogram 4302 as well,if discrimination between the particles of the specified size and otherparticles can be performed, particles of any size can be used. Thoughthis embodiment explains the case where the scroll bar 4303 wasemployed, if only the size of particles can be specified, any method canbe employed. The screen into which numerical values are input forspecification, for example, may also be employed. Though this embodimentexplained an example of displaying particles of the specified size orlarger, only the particles of the specified size may also be displayed,or the particles of the specified size or smaller may also be displayedas an alternative example of display.

Next, FIGS. 49 and 50 show examples of display indicating positioninformation and information on the sizes of particles and/or defectswhen classification into the particles and the defects is performed.

FIG. 49 comprises a graph 4901 where trace amounts obtained by theapparatus for inspecting particles and/or defects according to thepresent invention are plotted, position information 4902 on detectedparticles and/or defects, a detected particle and/or defect count 4903,and histograms 4904 showing the sizes of the detected particles and/ordefects. This embodiment shows the case where scratches are detected asthe defects.

Specifically, the trace amounts employed for the graph 4901 are theamounts of scattered light caused by vertical-illumination andoblique-illumination, respectively, as described with reference to FIGS.18A and 18B. Further, a line 4905 represents a discrimination thresholdfor discrimination between particles and scratches within the graph4901. The position information 4902 indicates the positions of particlesor scratches on an object under inspection. This embodiment shows anexample where particles are represented by ∘, and scratches arerepresented by ▴. Further, the detection count 4903 indicates the numberof detected particles and/or defects. The graphs 4904 are the histogramsshowing the numbers and the sizes of detected particles or scratches.Display of substances detected by the apparatus for inspecting particlesand/or defects according to the present invention in this way causes adistribution of particles and/or defects to be seen at a glance.

Next, FIG. 50 comprises position information 5001 on particles and/ordefects detected by the apparatus for inspecting particles and/ordefects according to the present invention, a detected particle and/ordefect quantity ratio 5002, and a density graph 5003 for given sizes ofparticles and/or defects. In this embodiment, pattern defects aredisplayed as the defects.

Specifically, the position information 5001 indicates the positions ofthe particles or pattern defects, and a closing line 5004 indicates aportion where particles or pattern defects are dense. Determination asto whether particles and/or defects are dense should be made accordingto whether a plurality of particles and/or defects is present in a givenarea. If a plurality of particles and/or defects is present in the givenarea, this area can be determined to the particle and/or defect densearea. The detected particle and/or defect quantity ratio 5002 indicatesthe ratio of the number of detected particles or pattern defects to thetotal number of detected particles and pattern defects, and an area in acircle graph corresponds to the ratio of the number of detectedparticles or pattern defects to the total number of detected particlesand pattern defects. This graph allows the ratio of particles and/ordefects detected by the apparatus for inspecting particles and/ordefects according to the present invention to be readily seen. The graph5003 showing the density and size of particles and/or defects indicatesthe portion where the particles and/or defects are dense, or adistribution of the density and size of the particles and/or defects inthe portion encircled by the closing line 504. This allows the densityand size of particles and/or defects in a dense area to be readily seen.

Next, a management approach applied when the statistics are collected intime series on particles having a particular size will be described withreference to FIGS. 9A to 9C.

FIG. 9A shows a transition of the total sum of all particles,irrespective of the size, detected by the particle inspection apparatus,in time series for wafers processed in the same process by the samemanufacturing apparatus. FIG. 9C shows a transition of the total sum ofparticles having sizes ranging from 2.8 to 3.0 [μm], shown in theexample of FIG. 7, in time series. FIG. 9B shows a transition of thetotal sum of the remaining particles in time series.

Thresholds 1001, 1002, 1003 indicate management reference values for thenumber of particles in the three cases. When particles exceeding thesethresholds are detected, this means that an associated wafer isdiagnosed as defective. Specifically, it is determined from FIG. 9A thata peak value 1004 near an inspection time A is unusually high.

However, while a certain failure may be guessed from the statisticsshown in FIG. 9A, its cause cannot be revealed.

On the other hand, when particles are managed by size in accordance withthe inspection approach of the present invention, a remarkable peak 1005appears at A time in FIG. 9C, so that it is understood that particleshaving sizes ranging from 2.8 to 3.0 [μm] particularly concentrate in alot which was inspected at that time. Thus, from the fact that nosection exceeds the threshold in FIG. 9B and the peak value 1005 issensed in FIG. 9C, the user can guess by the reason shown in FIGS. 5A to5C that patterns of these sizes peeled off and scattered on wafersduring an etching process can be the cause for an unusual increase inthe number of particles, and therefore immediately take effectivecountermeasures to the failure, such as checking the etching apparatus.

Next, an example of displaying a cause of failure to the user will bedescribed with reference to FIG. 11.

The apparatus for inspecting particles and/or defects according to thepresent invention has a function of analyzing the particle size and thenumber of detected particles to display a cause of failure to the user.

For example, assume that a graph as shown in FIG. 7 results from aninspection, taking the cause of failure shown in FIG. 5C as a model.Assume also that a section d-e in FIG. 5C corresponds to the particlesize range of 2.8 μm to 3.0 μm in FIG. 7. Therefore, when the result ofinspection shown in FIG. 7 is obtained, the screen shown in FIG. 10 isdisplayed to clarify the user the result of analysis on the cause offailure.

Particle Management Approach

Next described is another exemplary management approach based on theparticle size. Particles detected by the inspection apparatus may beclassified into those which cause a failure, and those which do notcause a failure. Specifically, if particles are smaller than wire widthsand spaces between wires in a wiring pattern created on a wafer, suchparticles cause no failure in many cases. Therefore, detected particleshaving a certain size or more may be managed as a possible cause offailure.

Next, description will be made on an exemplary method of calculating aparticle size to be managed. FIG. 23 shows the relationship between awiring pattern 2401 having a wire width W1, a wiring pattern 2402 havinga wire width W2 and a wiring pattern having a wire width W3 on a wafer,and a particle 2404. When this particle 2404 is conductive, the particle2404 attached, for example, at a position 2405 to connect the wiringpattern 2401 and wiring pattern 2402 would cause the wiring pattern 2401and wiring pattern 2402 to short-circuit through the particle 2404, withthe result that this chip becomes defective. As such, assuming that thedistance between the wiring pattern 2401 and wiring pattern 2402 is S1,and the distance between the wiring pattern 2402 and wiring pattern 2403is S2, the particle 2404 which can short-circuit the wiring pattern 2402to another wire has a size of S1 or S2 or more. Particularly, a particlehaving a size of (S1+W2+S2) will short-circuit wires with possibility of100%.

Therefore, when the wiring patterns have the widths and distance betweenwires as defined above, the particle size causing a failure is given by:MIN(S1,S2)where MIN (A, B) indicates the smaller value of A and B when they arecompared.

It should be noted that the example shown herein is a calculation forthe most strict condition in management. If the condition is lessstrict, larger particles may be managed.

By determining a particle size to be managed in each manufacturingprocess by the calculation described above and monitoring fluctuationsin the number of detected particles having the managed size or more, itis possible to sense the occurrence of a failure without delay. Amonitoring method used herein may involve previously calculating anaverage and standard deviation of the number of particles undermanagement detected, for example, from several to several tens ofwafers, monitoring the number of particles based on a monitoringthreshold calculated by:

Monitoring Threshold=Average+k·Standard Deviation and analyzing a causeof failure and taking countermeasures to wafers on which the number ofdetected particles exceeds the monitoring threshold. In the aboveequation, k is a constant which may be set to k=3, for example, when itis desired that the failure analysis is conducted for approximately 0.3%of all wafers.

Next described is another method of calculating a particle size to bemanaged. This method calculates the yield impact of particles exerted onthe yield of wafers from the presence or absence of particles detectedon one wafer, and determination made to chips (dies) on which theparticles are detected as to whether they are non-defective ordefective, and manages a particle size at which the calculated influencepresent a maximum.

A method of calculating the yield impact will be described withreference to FIG. 29. FIG. 29 shows chips (dies) on a wafer classifiedaccording to the presence or absence of particles, and non-defective anddefective chips. Specifically, FIG. 29 shows chips 3001 (hereinafterlabeled “Gn”) on which no particles have been detected and which arenon-defective (good dies); chips 3002 (hereinafter labeled “Bn”) onwhich no particles have been detected but which are defective (baddies); chips 3003 (hereinafter labeled “Gp”) on which particles havebeen detected but which are non-defective; and chips 3004 (hereinafterlabeled “Bp”) on which particles have been detected and which aredefective. Here, whether or not particles have been detected on acertain chip may be determined based on the position information in theresult of an inspection performed by the apparatus for inspectingparticles and/or defects according to the present invention. Also,determination as to whether a certain chip is non-defective or defectivemay be made using, for example, the result of an electric inspection.

First, assuming that the yield of a certain wafer is Y, and the yield ofchips on which no particles have been detected is Yn, the yield impactdY of detected particles on the yield of the wafer is defined as:dY=Yn−YSince Y is the yield of the wafer, Y can be expressed by:Y=Yn·(1−γ)+Yp·γwhere Yp is the yield of chips on which particles have been detected,and γ is the proportion of chips on which particles have been detectedwith respect to the total number of chips (hereinafter called the“particle occurrence frequency”).

Here, using the aforementioned Gn, Bn, Gp, Bp:Y=(Gn+Gp)/(Gn+Bn+Gp+Bp)Yn=Gn/(Gn+Bn)Yp=Gp/(Gp+Bp)γ=(Gp+Bp)/(Gn+Bn+Gp+Bp)can be derived.

Therefore, dY can be expressed as follows:

$\quad\begin{matrix}{{dY} = {{Yn} - Y}} \\{= {{Yn} - \left( {{{Yn} \cdot \left( {1 - \gamma} \right)} + {{Yp} \cdot \gamma}} \right)}} \\{= {\left( {{Yn} - {Yp}} \right) \cdot \gamma}} \\{= {{Yn} \cdot \left( {1 - {{Yp}/{Yn}}} \right) \cdot \gamma}}\end{matrix}$Here, assuming that the probability of a chip determined as defectivedue to particles is represented by F (hereinafter called the “criticalprobability”), Yp can be expressed by:Yp=Yn·(1−F)

Rewriting the above equation for F,F=1−Yp/Ynso that dY can be expressed by:dY=Yn·F·γ

Here, the particle occurrence frequency γ is larger as a particledetection sensitivity is higher, and smaller as the particle detectionsensitivity is lower. This is because a higher detection sensitivitycontributes to detection of a larger number of particles. The criticalprobability F in turn is smaller as the particle detection sensitivityis higher, and larger as the particle detection sensitivity is lower.This is because although a higher sensitivity contributes to detectionof smaller particles, those particles which are smaller than thedistance between wiring patterns do not cause a failure such asshort-circuiting.

Therefore, when the yield impact dY on the yield is calculated, theparticle sizes used in the calculation are limited. The particle sizewhich maximizes the yield impact dY on the yield indicates the minimumparticle size to be managed. The limitation on the particle sizes refersto using those data on particles having a certain size or more.

Details of the method of calculating the yield impact will be describedwith reference to FIG. 51. In a graph 5101, the yield impact dY on theyield is plotted on the vertical axis, while the particle size thresholdis plotted on the horizontal axis. The particle size threshold hereinrefers to the threshold for all the particles of a certain size orlarger. Specifically, referring to FIG. 51, a particle size threshold5102 indicates the case where calculation is performed by using the dataon particles having sizes equal to or more than “A” μm. The yield impactat that time is indicated by a point 5103, and the result of particledetection at that time, or the result of detection of particles havingsizes equal to or more than “A” μm is indicated by an inspection result5104.

Likewise, a particle size threshold 5105 indicates the case wherecalculation is performed by using data on particles having sizes equalto or more than “B” μm. The yield impact at that time is indicated by apoint 5106, and the result of particle detection at that time isindicated by an inspection result 5107. Further, a particle sizethreshold 5108 indicates the case where calculation is performed byusing data on particles having sizes equal to or more than “C” μm. Theyield impact is indicated by a point 5109, and the result of particledetection at that time is indicated by an inspection result 5110.

A graph 5111 is obtained by calculating the yield impact by means ofrespective particle size thresholds. Since calculation is performedaccording to the above-mentioned approach, the graph 5111 represents theinfluences of the respective particle sizes on the yield. Accordingly,the particle size threshold with a high yield impact represents theparticle size whereby particles that affects the yield can beefficiently performed. In this sense, it is the particle size to bemanaged on the semiconductor device manufacturing line. Specifically,referring to FIG. 51, since a plot point 5112 on the graph 5111indicates the maximum value of calculation, the above-mentioned minimumparticle size to be managed becomes a particle size threshold 5113.

FIG. 24 shows an exemplary result of calculating the yield impact dY onthe yield. FIG. 24 shows the yield impact dY on the yield on thevertical axis, and the particle size used in calculating the yieldimpact dY on the yield on the horizontal axis. For example, in FIG. 24,a point 2501 indicates that the yield impact dY on the yield is 0.1 as aresult of the calculation using data on particles having sizes equal toor more than 0.1 μm, and a point 2502 indicates that the yield impact dYon the yield is 0.8 as a result of the calculation using data onparticles having sizes equal to or more than 0.4 μm. Here, using data onparticles having the sizes equal to or more than 0.1 μm means that thecalculation is performed on the assumption that among detectedparticles, chips on which particles of 0.1 μm or more have been detectedare regarded as chips on which particles are attached, and chips onwhich particles less than 0.1 μm have been detected or no particles havebeen detected are regarded as chips on which no particles are attached.Thus, it is appreciated from FIG. 24 that the yield impact dY on theyield is the largest when it is calculated using data on particles of0.4 μm or more, so that particles of 0.4 μm or more should be managed.

FIG. 52 shows an example of the yield impact dY on the yield for eachstep. FIG. 52 shows a graph 5201 obtained as a result of calculationusing data in step 1, a graph 5202 obtained as a result of calculationusing data in step 2, and a management particle size display 5203.Referring to FIG. 52, step 1 shows the case where particles having sizesequal to or more than 0.3 μm should be managed, while step 2 shows thecase where particles having sizes equal to or more than 0.7 μm should bemanaged.

While the foregoing embodiment shows that the particle size is changedin increments of 0.1 μm, the increment may be 0.2 μm or any other value.Also, while the foregoing embodiment has been described for an examplewhich determines the particle size that exerts the largest yield impactdY on the yield as the method of determining a particle size to bemanaged, the particle size to be managed need not be the particle sizethat exerts the largest influence, but may be a particle size thatpresents a value close to the largest yield impact dY on the yield, forexample, a value equal to or more than the largest yield impact dYmultiplied by 0.9.

FIGS. 33A to 33C show another exemplary result of calculation. FIGS. 33Ato 33C show the result of calculating the yield impact dY on the yield;and particle detection maps at that time. FIG. 33A shows, by way ofexample, that the yield impact dY on the yield is calculated inincrements of approximately 0.07 μm of particle size, and values on thevertical axis are represented in percent. FIG. 33B is a particledetection map which displays all particles detected by the apparatus forinspecting particles and/or defects according to the present invention,and FIG. 33C is a particle detection map which shows extracted particleshaving the sizes equal to or more than 1.1 μm. The value of 1.1 μmindicates the particle size that exerts the largest yield impact dY onthe yield in FIG. 33A. It is therefore understood that particles may bemanaged based on the particle detection map of FIG. 33C.

In this embodiment, though description was directed to the use of dataon a single wafer, the yield impact dY on the yield may also becalculated separately using data on a plurality of wafers. Then, theaverage value of the yield impact dY may be defined as the typical valueof the yield impact dY on the yield. This method is advantageous in thaterroneous evaluation due to the data on a special wafer can be reduced.Alternatively, the sizes of particles to be managed may be calculatedusing data on a plurality of wafers, and the minimum particle size valuefor a certain step may be defined as the particle size to be managed forthe stverticaln this case, the management that is more strict than theone using the data on a single wafer becomes possible, which can lead toimprovement in the quality of semiconductor devices.

Further, if the number of chips on a wafer is small, the accuracy ofcalculating the yield impact dY on the yield is sometimes reduced. Thus,when calculating the yield impact dY on the yield, data on a pluralityof wafers may also be employed.

Next, description will be made on an approach for managing asemiconductor device manufacturing process when the yield impact dY onthe yield is used for the management. FIG. 25 shows a graph which setsthe aforementioned yield impact dY on the yield on the vertical axis,and a semiconductor manufacturing process on the horizontal axis.Specifically, the horizontal axis shows steps in the process in whichparticles are inspected using the apparatus for inspecting particlesand/or defects according to the present invention.

Next, the operation will be described. First, an inspection is conductedin each of the steps in the process shown on the horizontal axis usingthe same wafer. Next, at the time each of chips on the wafer isdetermined as non-defective or defective, the aforementioned yieldimpact dY on the yield is calculated for each step. FIG. 25 is anexample of calculating the yield impact dY on the yield in each step.For example, a point 2601 indicates that the yield impact dY on theyield is 0.8 when calculated using particles detected in a step labeled“Step 4” in the process. In this way, the yield impact dY on the yieldis calculated in each step, and countermeasures are taken preferentiallyfrom a step which presents a larger yield impact dY on the yield,thereby making it possible to take countermeasures from a step which ismore likely to cause a failure.

In the foregoing embodiment, all data on particles detected in each stepare used for calculating the yield impact dY. For particles which havebeen known that they had occurred in a different step, the yield impactdY on the yield may be calculated using the remaining data except forthe data on the particles. For removing data, for example, informationon the position of particles detected in Step 1 in FIG. 25 may becompared with information on the position of particles detected in Step2, and the particles previously detected in Step 1 may be deleted fromdata on particles in Step 2.

Also, the foregoing embodiment has been described for the management ofparticle size using the yield impact dY on the yield expressed by:dY=Yn·F·γWhen a failure caused by a process is eliminated by improving theprocess management,dY=F·γmay be used by setting the aforementioned Yn to one (Yn=1). The approachof the present invention may also be applied to any index forcalculating the influence of particles. For example, for memory productssuch as DRAM, the number of defective bits caused by each particle maybe used as an index. Further, in the case of a chip on which particleshave been detected, a proportion of non-defective chips on whichparticles have been detected, or the above-mentioned Yp may also be usedas the index. Alternatively, the number of chips on which particles havebeen detected, or the above-mentioned γ may also be used as the index,or the critical probability F may also be used as the index. When usingthe indexes of Yp and F, the influence of particles can be directlycalculated, and when using the index of γ, the influence of particlescan be calculated immediately after inspection. Alternatively, the valueof (Y−Yp) may also be used as the index, and the value of (Yn−Yp) mayalso be used as the index.

FIG. 53 shows an example of displaying calculated dY, F, and γ.Referring to FIG. 53, a graph 5301 is obtained by calculating the dY onthe yield, while the graph 5302 represents the critical probability F.Further, the graph 5303 is obtained by calculating the proportion γ ofchips on which particles have been detected.

In this embodiment, data on particles having sizes equal to or more thana certain size is employed as the data for calculating the yield impactdY on the yield. For the calculation, the data on particles of a givensize may also be employed. In this case, since the influence on theparticles of the given size can be evaluated, accurate evaluationbecomes possible.

Alternatively, the yield impact dY on the yield may also be calculatedaccording to the shape of a particle described before. This method isadvantageous in that efficient countermeasures can be taken. That is,the shape of a particle is often associated with the cause ofoccurrence. Thus, it is important to define the shape of a particleagainst which countermeasures should be taken. By preferentially takingcountermeasures against a particle having the shape that greatly affectsthe yield impact dY on the yield according to the approach of thepresent invention, countermeasures against defective semiconductordevices can be efficiently performed.

The foregoing embodiment is advantageous in that since wiring patternwidths and space widths in a semiconductor device are only required asinformation for determining whether a particle causes a failure in theexample described with reference to FIG. 23, a particle size to bemanaged can be determined at the time the design of a semiconductordevice is definite. The example described with reference to FIG. 29, inturn, is advantageous in that it employs an index including aconsideration of information such as short-circuiting of wires due tothe height of a particle, and so on, as well as the width of theparticle, so that the actual state of device can be known.

Next, an example of display using the above-mentioned yield impact dY onthe yield will be shown in FIG. 54. In FIG. 54, the particle sizethreshold is plotted on the horizontal axis, and the yield impact isplotted on the vertical axis. FIG. 54 includes a graph 5401, a detectionresult 5402, and a detected particle count 5403.

Referring to FIG. 54, the graph 5401 is obtained by connecting thevalues of the yield impacts for the respective particle thresholds. Thedetection result 5402 and the detected particle count 5403 indicate theresults of particle detection and the number of detected particles for aparticle size threshold 5404. Incidentally, in this embodiment, only acombination of the result of detection and the number of detectedparticles for the given particle size threshold is displayed. However,other combination of the result of inspection and the number of detectedparticles for other particle size threshold may be additionally providedfor display.

The foregoing description was directed to the approach for determiningfrom a detected particle a size to be managed. This approach can beapplied irrespective of whether other detected substances exceptparticles and/or defects are present or not. In other words, thisapproach is effective in an inspection performed on in both of the caseswhere the apparatus for inspecting particles and/or defects erroneouslydetects normal patterns and where the apparatus does not erroneouslydetect normal patterns. Accordingly, strict settings of inspectionconditions does not need to be performed for the apparatus forinspecting particles and/or defects, so that settings of inspectionconditions becomes simplified or unnecessary.

Inspection on Particles by Region and Analysis on Cause of Failure

Next, description will be made on an embodiment which manages particledata by region on a wafer to take countermeasures using the apparatusfor inspecting particles and/or defects according to the presentinvention.

FIG. 11 schematically illustrates regions on a semiconductor wafer.

FIGS. 12A, 12B are schematic diagrams each clearly showing particles ofa particular size on a wafer when particle data is managed separatelyfor each region;

FIGS. 13, 14 are graphs each showing the number of detected particles bysize in each region.

Generally, when a chip pattern is formed on a semiconductor wafer, thepattern is not always formed uniformly, but some region in the patternexhibits a higher pattern forming density while another region in thepattern exhibits a lower pattern forming density. For example, assumingthat a chip illustrated in FIG. 11 is a microprocessor, the pattern isdivided, for example, into a region 1101 for memory cell circuits; aregion 1102 for data input/output circuits; and a region 1103 in whichno circuit pattern exists. Generally, these regions 1101, 1102, 1103differ in circuit pattern integration degree from one another. As aresult, different sizes of particles would cause failures in therespective regions. In other words, the particle size which should bemanaged and analyzed differs from one region to another in a chip.

Specifically stated, for example, when a particle of size α or morewould cause the chip to be defective in the region 1101; a particle ofsize β or more in the region 1102; and a particle of size γ or more inthe region 1103, information on these regions and information onparticle size which causes the chip to be defective in each of theseregions are previously stored in the inspection apparatus as managementdata. The information on the regions and information on particle sizecausing the defective chip may be directly entered on a screen which maybe provided on the inspection apparatus for entering coordinate valuesand particle size, or regions may be selected from an optical imagecaptured by a TV camera or the like. Alternatively, data may bedownloaded from a higher rank system, or data may be read into theinspection apparatus from a removable storage medium, for example, afloppy disk.

By providing the inspection apparatus with the information on theregions and the information on particle sizes which cause the chip to bedefective, an object under inspection is inspected. Then, a region isdetermined from information on the position of a detected particle inthe inspection apparatus, and the information on the detected particlesize is compared with the information on particle sizes which cause thechip to be defective, to determine whether or not the detected particlewill cause a failure.

As a result, particles determined as a cause of failure and particlesnot determined as a cause of failure are displayed in different forms,such that the particles determined as a cause of failure aredistinctively displayed to the user, thereby allowing the user to beimmediately aware of the particles which cause a failure.

The foregoing approach will be shown in a specific manner with referenceto FIGS. 12A, 12B.

A wafer shown in FIGS. 12A, 12B is displayed with the positions ofdetected particles 1202 indicated thereon. Since the result of detectionhas been displayed as shown in FIG. 12A in the prior art, an analysis onthe cause of failure involves selecting proper particles and analyzingthe selected particles. Therefore, the prior art suffers from a lowprobability that particles which should be essentially analyzed can beselected, and a long time required for the analysis on the cause offailure. On the contrary, by displaying in a different form thoseparticles which have been determined as the cause of failure using theforegoing determination, i.e., particles 1203 which should be analyzedas shown in FIG. 12B, it is possible to readily select the particles1203 which should be analyzed from detected particles, to increase theprobability that the particles which should be analyzed can be selected,and to rapidly analyze the cause of failure. In FIG. 11, for displayingdifferent regions in different manners, they are displayed in differentpatterns. Alternatively, these region may be displayed in differentcolors or sizes. Further alternatively, displayed particles may belimited to those which cause a failure. Also, while the foregoingembodiment divides a chip into several regions, the wafer surface may bedivided, for example, in accordance with the distance from the center ofthe wafer to the wafer edge, and different particle sizes may be managedin different regions. Furthermore, the layout of semiconductor chips maybe displayed on the wafer shape 1201.

Next, description will be made on an approach for inspecting the numberof particles detected in respective regions to take countermeasures to afailure with reference to FIGS. 13 and 14.

In this example, a wafer is divided into three regions, designatedRegion A, Region B, Region C, in each of which the number of particlesis detected. Then, the result is displayed to the user in the form ofgraph for each region.

For example, as shown in FIG. 13, the horizontal axis represents theparticle size, and the vertical axis represents the number of detectedparticles, wherein different colors are allocated to Region A, Region B,Region C, respectively, the particles are displayed by size in graphicalrepresentation, and the numbers of particles falling under the same sizecategory in the three regions are displayed side by side.

Alternatively, as shown in FIG. 14, the numbers of particles fallingunder the same size category may be displayed in stack.

Specifically, the three regions may be a memory cell region, a circuitregion other than memory circuit, and region without circuit pattern,for example, on a semiconductor wafer. By displaying these regions asshown in FIGS. 13 and 14, the management of particles by region isfacilitated. The information on the regions may be directly entered on ascreen which may be provided on the inspection apparatus for enteringcoordinate values and particle size, or regions may be selected from anoptical image captured by a TV camera or the like. Alternatively, datamay be downloaded from a higher rank system, or data may be read intothe inspection apparatus from a removable storage medium, for example, afloppy disk.

Next described will be an approach for counting the number of detectedparticles by size in each of regions to find out defective products.

As described above, the particle size determined as a cause of failurediffers from one region to another. In a certain region which does notinclude very fine circuits, even a relatively large particle would notbe regarded as a cause of failure. On the other hand, in another regionwhich includes fine circuits, even a relatively small particle couldcause a trouble. In this way, thresholds over which an alarm isgenerated are designated by α, β, γ for Region A, Region B, Region C,respectively. For example, in the example shown in FIGS. 13, 14, assume:

α=1.0 [μm]

β=1.6 [μm]

γ=2.0 [μm]

With these thresholds, the total sum of detected particles exceeding thethreshold set for each region is as follows:

Region A . . . 24

Region B . . . 3

Region C . . . 1

Even though a very large number of particles are apparently detected inRegion C, they do not significantly affect the quality of a product. Onthe other hand, particles detected in Region A, the number of which isnot so large as in Region C, is highly likely to affect the quality ofthe product, so that the product could be determined as defective due tothe particles attached on Region A with a high probability. In this way,a reasonable inspection can be conducted in accordance with thecharacteristic of each region by setting a threshold of particle sizefor each region, over which a particle detected therein is regarded as acause of failure, counting the total sum of detected particles exceedingthe threshold in each region, determining whether the object undertesting is non-defective or defective, and displaying the user to theresult of determination.

Device Performance Evaluation Approach Using Particle Size

Next, an approach to evaluating an inspection apparatus according to thepresent invention will be described.

FIGS. 55A and 55B are graphs in which the yield impact is calculated foreach device or for each detection sensitivity. In FIGS. 55A and 55B, theabove-mentioned yield impact is plotted on the vertical axis, and theparticle size threshold is plotted on the horizontal axis.

Next, the evaluation approach will be described. First, the same objectsunder inspection are inspected by inspection apparatuses to beevaluated, and then the graphs of FIGS. 55A and 55B each indicating theyield impact for each particle size threshold are created. FIGS. 55A and55B are examples of the graphs thus created.

FIG. 55A shows a graph 5501 as a result of calculation by an inspectionapparatus A and a graph 5502 as a result of calculation by an inspectionapparatus B. Referring to FIG. 55A, the minimum particle size thresholdsfor both of the inspection apparatuses are approximately 0.6 μm.However, the yield impact calculated by the inspection apparatus A islarger than that calculated by the inspection apparatus B. This isbecause the inspection apparatus A detects more particles that affectthe yield. In other words, the inspection apparatus B would have a lowerparticle capturing ratio than the inspection apparatus A. Accordingly,the inspection apparatus A is more suited to the object under inspectionemployed in this embodiment than the inspection apparatus b.

Next, FIG. 55B comprises a graph 5501 as a result of calculation by theinspection apparatus A and a graph 5503 as a result of calculation by aninspection apparatus C. Referring to FIG. 55B, for the particle sizethresholds smaller than 1.3 μm, the yield impact is of approximately thesame level in both of the apparatuses. However, in regard to theinspection apparatus C, there is no data for the particle size thresholdsmaller than 1.3 μm. This is because the inspection apparatus C does notdetect particles of sizes smaller than 1.3 μm. In other words, theinspection apparatus C does not have sufficient detection sensitivity.Accordingly, for the object under inspection employed in thisembodiment, the inspection apparatus A is more suitable for inspectionthan the inspection apparatus C.

With the approach as described above, evaluation of the performance ofan inspection apparatus becomes possible. Further, by performing theevaluation for each of the processes, the optimal inspection apparatusfor each of the processes can be selected.

In the embodiment described above, description was directed to theevaluation approach where graphs have been created. However, it is notalways necessary to create graphs. The maximum value of the yield impactmay be determined, and then evaluation may be performed using themaximum value. In this embodiment, though the yield impact is used as anevaluation index, other indexes used when the approach for determiningthe management particle size was described may also be used forevaluation. Further, if an inspection apparatus to be evaluated does nothave a function of outputting data on the size of a particle and/or adefect, the result of inspection by the apparatus may be reviewed by thereview apparatus, and then the size of the particle and/or defect mayalso be determined.

FIG. 56 shows examples of evaluations of three inspection apparatuses.FIG. 56 shows graphs in which the yield impact were calculated by thethree inspection apparatuses, and graphs 5601, 5602, and 5603 are theresults of calculation by the respective three inspection apparatuses.By displaying the results of calculation by a plurality of inspectionapparatuses as shown in FIG. 56, the performance of the inspectionapparatuses can be readily seen.

About Display

About display according to the present invention described above,display may be performed on the apparatus for inspecting particlesand/or defects according to the present invention. Alternatively,display may also be performed on a terminal connected to a host system.In this case, display on the terminal of the host system is advantageousin that the result of inspection can be seen on any terminal connectedto the host system.

About Optical System in Apparatus for Inspecting Particles and/orDefects

In the foregoing description on the present invention, the opticalsystem in the apparatus for inspecting particles and/or defects employsscattered light to detect particles and measure the sizes of theparticles. The approach of the present invention, however, can beapplied to an optical system which relies on reflected light to detectparticles and/or defects and measure the sizes thereof. Generally, theoptical system relying on scattered light exhibits a high inspectionefficiency but a low measurement accuracy. On the contrary, the opticalsystem relying on reflected light exhibits a low inspection efficiency,but a high measurement accuracy. The approach of the present inventioncan be applied to either of the optical systems.

As appreciated from the foregoing, the present invention provides anapparatus and method for inspecting particles ore defects, which aresuitable for use in inspecting particles and/or defects in processes formanufacturing semiconductor wafers or thin film substrates andconducting a failure analysis based on the inspection result. Theinspection apparatus and method are capable of rapidly takingcountermeasures to a failure by conducting an inspection and a failureanalysis in accordance with the characteristics of particles andpatterns or the characteristics of regions on an object underinspection.

The invention may be embodied in other specific forms without departingfrom the spirit or essential characteristics thereof. The presentinvention is therefore to be considered in all respects as illustrativeand not restrictive, the scope of the invention being indicated by theappended claims rather than by the foregoing description and all changeswhich come within the meaning and range of equivalency of the claims aretherefore intended to be the embraced therein.

1. An apparatus for inspecting particles and/or pattern defects of anobject under inspection, the apparatus comprising: illuminating meansfor irradiating the object under inspection with light; light detectingmeans for detecting scattered light from the object under inspectioncaused by irradiation of the light by said illuminating means; detectingmeans for processing signals obtained by detection of the scatteredlight by said light detecting means to detect particles and/or thepattern defects for each of a plurality of inspection areas, based oncriteria associated with the plurality of inspection areas, theplurality of inspection areas being obtained by dividing the objectunder inspection; data processing means for obtaining information onsizes of the particles and/or the pattern defects, information onclassification of the particles and/or the pattern defects, andinformation on occurrence frequencies of the particles and/or thepattern defects for each of the plurality of inspection areas, based oninformation on said each of the particles and/or the pattern defectsdetected by said detecting means for each of the plurality of inspectionareas; and display means for displaying the information on theoccurrence frequencies for each size classification of the particlesand/or the pattern defects for said each of the plurality of inspectionareas, obtained by processing by said data processing means; wherein thedata processing means obtains information on size of the particlesand/or the pattern defects from an intensity of the scattered lightdetected by the light detecting means by calculating an integral ofintensity over particle and/or pattern detect data and, in case theintensity is saturated, calculating a volume of an intensity signal oversaid saturated area by using information of the intensity of thescattered light detected over said particle and/or pattern detect data.2. An apparatus according to the claim 1, wherein said calculation iscarried our by assuming that a waveform of the intensity saturatedportion has a shape of Gaussian distribution if it is not saturated. 3.An apparatus according to the claim 1, wherein said detecting meansprocesses said signals to detect particles and/or the pattern defects bycomparing said signals with reference signals to extract differencesbetween them.
 4. An apparatus according to the claim 1, wherein saidilluminating means irradiates the object under inspection with anultraviolet laser.
 5. An apparatus according to the claim 1, whereinsaid illuminating means is a semiconductor laser.
 6. A method ofinspecting particles and/or pattern defects of an object underinspection, comprising: irradiating the object under inspection withlight; detecting light scattered from the object under inspection causedby the irradiation with the light; processing signals obtained by thedetection of the scattered light to detect particles and/or patterndefeats; obtaining information on size of the particles and/or thepattern defects information on classification of the particles and/orthe pattern defects, and information on occurrence frequencies of theparticles and/or the pattern defects based on information on said eachof the particles and/or the pattern defects; and displaying theinformation on the occurrence frequency for each size classification ofthe particles and/or the pattern defeats, wherein in the obtaininginformation on size of the particles and for the pattern defects from anintensity of the scattered light, calculating an integral over particleand/or pattern defect data and, in case the intensity signal issaturated, calculating a volume of an intensity signal over saidsaturated data by using information of the intensity of the scatteredlight detected over said particles and/or the pattern defect data.
 7. Amethod according to the claim 6, wherein said obtaining information onsize of the particles and/or the pattern defects is carried out byassuming that a waveform of the intensity saturated portion has a shapeof Gaussian distribution if it is not saturated.
 8. A method accordingto the claim 6, wherein said processing includes processing said signalsto detect particles and/or the pattern defects by comparing said signalswith reference signals to extract differences between them.
 9. A methodaccording to the claim 6, wherein in said irradiating, the object underinspection is irradiated with an ultraviolet laser.
 10. A methodaccording to the claim 6, wherein in said irradiating, the object underinspection is irradiated with a semiconductor laser.